ENGIE Services Singapore is a leading provider of Integrated Facilities Management solutions (IFM), property management, operations and maintenance, specialized rail engineering works, sustainable solutions and FM Consultancy services. With strong presence in various counties across South East Asia, we operate across mission-critical industries - aviation, transportation, healthcare, education, government and commercial.

ENGIE understands the integrated role of facility management and the value of it can be expanded beyond the traditional approach. As a total FM, specialized engineering and sustainable real estate solutions service provider, ENGIE offers a comprehensive range of technical, digital and support services customisable to best suit your unique needs.

Job Description:

• Monitor, maintain and coordinate the operations of data centre electrical/ mechanical infrastructure and building monitoring systems.
• Conduct daily site inspections, record readings and data logging of data centre equipment to ensure proper operation and checklist verification.
• Provide 24X7 first level onsite response to any M&E incident accordingly to contractual obligation.
• Perform troubleshooting of mechanical and electrical equipment malfunctions and perform ad-hoc repair as and when necessary.
• Report operations abnormality and perform escalation with follow-up on improvement plan promptly.
• Create quotation, work orders, coordinate vendor/supplier repairs/replacement on the data centre sites.
• Adhere to data centre operations work rules, policies and procedures that include but not limited to emergency operating procedures (EOPs), emergency drill procedures, standard operation procedures (SOPs), methods of procedures (MOPs) incident management, maintenance management, vendor management and document control standards.
• Maintain proper documentation and service reports are filed and submitted to customers for auditing and tracking purposes.
• Plan the annual master planned preventive maintenance schedules and provide guidance for addition to, deletion or modification of existing maintenance routines.
• Maintain and monitor the appropriate key performance indicators (KPIs) and external service level agreements (SLA's) to measure and improve onsite operations
• Oversee the execution of planned maintenance works performed by appointed vendors/subcontractors to ensure maintenance meets satisfactory level and are in accordance with the signed contract agreement.
• Provide onsite support to customer requests, incidents, can change and problem management activities.
• Manage and handle ticket management and queue monitoring.
• Schedule weekly meetings with customer and its appointed subcontractors with proper minutes taken to review and discuss service levels, operational issues as well as planning for future work.
• Prepare customer weekly progress report and track status of deliverables.
• Prepare incident report accordingly to contractual service level agreement.
• Support yearly performance review session with customer.
• Coordinating all changes to the DC infrastructure that may affect the service levels of any other service areas within the DC premises.
• Accountable for all site inventory management such as tools, test equipment, replacement parts, materials, spare parts and consumables used and sorted at the site.
• Adherences to all quality, health & safety, environmental policies and customer house riles.
• Perform any other ad-hoc tasks associated with the maintenance, upgrading, repairs, addition or modification of the facilities, as instructed by the management.
• Ensure that all information security management system related policies, procedures and specified requirements are implemented and complied to.
• Any other tasks as assigned by the supervisor.

Requirements:

• At least a Post Graduate Diploma in Engineering (Electrical/Electronic), Engineering (Industrial), Engineering (Mechanical) or equivalent
• Minimum 3 years Data Centre facilities experience
• Operational experience with critical facility equipment/ system that includes but not limited to transformers, generators, DRUPS, UPS, PDU, Chiller System, CRAH and Fire System
• Work independently with minimum of supervision
• Analytical and problem-solving skills
• Good organizational skills with the ability to maintain all facility related documentation. Detailed and careful in submissions and reporting
• Proficient in Microsoft Office
• Has a good safety mindset and displays good WSH behaviour

We are seeking a skilled Data Centre Engineer to manage the day-to-day operations and maintenance of our data center facilities. The ideal candidate will have a strong background in building technologies, mechanical and electrical services, as well as experience in data center facility and vendor management.

Key Responsibilities:

• Manage the operations and maintenance of data center facilities, ensuring all systems are running efficiently.
• Oversee the mechanical, electrical, and building systems, ensuring they meet the performance and sustainability standards.
• Collaborate with vendors to manage and optimize service contracts, ensuring timely and efficient service delivery.
• Coordinate and ensure proper project execution for new installations or upgrades.
• Provide support for troubleshooting and resolving technical issues in the facility.
• Implement and maintain best practices in facility management, ensuring regulatory compliance and safety standards are met.
• Track and monitor facility performance, ensuring optimal uptime and operational efficiency.
• Work closely with internal teams to plan and execute preventive maintenance tasks.
• Ensure effective communication with stakeholders, including internal teams and external vendors.

Skills and Qualifications:

• Strong knowledge of building technologies, mechanical and electrical systems, and facilities management.
• Proven experience in data center facility management and vendor management.
• Excellent interpersonal and communication skills.
• Project management experience is preferred.
• Ability to manage multiple tasks and track job progress effectively.
• Problem-solving mindset with a focus on efficiency and uptime.

(EA Reg No: 20C0312)

Only shortlisted candidates will be notified

Please email a copy of your detailed resume to [email protected] for immediate processing.

• 5+ years of AI and Data consulting experience, or other relevant experience in AI & Analytics domain, with a proven track record of building and maintaining client relationships
• Collaborate with customers and account partners to identify new AI opportunities, and build proposals and pitch materials to position as a trusted partner for AI & Data transformation
• Organize and lead educational and ideation AI and Generative AI workshops for customers
• Understand customer's needs and assess their AI maturity
• Evaluate and recommend appropriate AI frameworks, tools and platforms
• Lead AI feasibility studies and PoC projects to demonstrate the value and viability of AI solutions
• Develop end to end AI PoC projects using Python, Flask, FastAPI and Streamlit
• Have experience in cloud services of AWS / GCP / Azure to deploy AI products
• Collaborate with AI architects and engineers to design and develop AI and Generative AI solutions tailored to the clients’ requirements
• Lead integration and deployment of AI solutions into customers’ existing infrastructure
• Stay updated with the latest advancements in AI and Generative AI technologies, trends and best practices and develop thought leadership and PoV on AI
• Work with cross-functional team and partners to develop/ enhance and package AI offerings and assets for customer-facing discussions
• In-depth understanding of AI technologies, including machine learning, deep learning, and generative AI techniques (such as generative adversial networks (GANs), variational autoencoders (VAEs), etc.)

Department: Data Engineering

Reports To: Consulting Manager/Project Manager

Location: Remote/Hybrid (Singapore)

About VASS

VASS is a global digital transformation company that puts organizations at the forefront of innovation, by bringing together talent, knowledge, and technology. With our digital solutions, we lead people and organizations around the world on their transition towards the future.

About the Role

We are seeking a highly motivated and skilled Snowflake Data Engineer to join our dynamic Consulting team. In this client-facing role, you will be responsible for leading and delivering successful Snowflake data warehousing and data engineering projects for our diverse clientele. You will work closely with clients to understand their business requirements, design and implement robust data solutions, and ensure successful project delivery.

Responsibilities

· Lead and deliver end-to-end Snowflake implementation projects, including data discovery, data modeling, data integration, data quality, and performance optimization.

· Work closely with clients to gather requirements, understand business needs, and translate them into technical solutions.

· Design, develop, and implement data pipelines using Snowflake and other relevant technologies (e.g., Python, SQL, APIs) to extract, transform, and load (ETL) data from various sources into the Snowflake data warehouse.

· Optimize data models and queries for performance and efficiency within the Snowflake environment.

· Develop and implement data quality checks and monitoring processes to ensure data accuracy and integrity.

· Troubleshoot and resolve data-related issues and performance bottlenecks.

· Participate in the design and implementation of data security and governance best practices within the Snowflake environment.

· Guide clients on best practices for data warehousing, data engineering, and Snowflake utilization.

· Develop and maintain CI/CD pipelines for Snowflake data pipelines and ETL processes.

· Provide knowledge transfer to clients. Prepare and deliver presentations and reports to clients.

Qualifications

• Bachelor’s degree in computer science, Computer Engineering, or a related field.
• 3+ years of experience as a Data Engineer or a similar role.
• Strong experience with Snowflake data warehousing and its core features (e.g., SQL, data loading, data sharing, security).
• Proficiency in Python and SQL.
• Experience with data modeling and data warehousing concepts.
• Experience with ETL/ELT processes and tools.
• Experience with data quality and data validation techniques.
• Experience with data security and governance best practices.
• Experience with CI/CD principles and tools (e.g., Jenkins, GitHub Actions, Azure DevOps).
• Experience with integrating Snowflake deployments into CI/CD pipelines.
• Excellent analytical and problem-solving skills.
• Strong communication and collaboration skills
• Ability to work independently and as part of a team.

Benefits

· Competitive Salary

· Hybrid/Remote Working Model

· Competitive compensation package

· Comprehensive benefits package

· Opportunities for professional development and career advancement

· A collaborative and innovative work environment.

If you are a passionate and driven individual, we encourage you to apply and help us shape the future of enterprise software!

Please send your job application, along with a recent photo, to [email protected] . Kindly include your earliest available start date and both your current and expected salary. We look forward to hearing from you!

Qualifications

• 5 - 7 years of IT Security experience in administration and management of IT Security technologies primarily Endpoint Protection, Email Security and DLP, Data Classification and other endpoint & data security solutions;
• Knowledge of different domains of IT Security;
• Working & hands-on experience in administering the IT Security Solutions;
• Must have experience in working in similar Production setup in Run (Operations) mode;
• Ability to apply risk based approach while working on assigned responsibilities;
• Hands-on experience on Symantec Data Loss Prevention (DLP);
• Highly proficient overall security solutions like, Endpoint Protection, Email Security and Vulnerability Management;
• Deployment, integration and administration experience of various components of Symantec DLP:

- Symantec Endpoint Protect

- Symantec Web Prevent

- Symantec Email Prevent

- Symantec Enforce

• Experience in defining, designing and configuring DLP Policies as per the business requirements;
• Deploy, upgrade and troubleshooting knowledge on Symantec DLP solution;
• Deploy, Upgrade and troubleshoot on DAM Solutions like IMPERVA or Guardium
• Expertise knowledge in Email Security Solutions
• Hands-on to Expertise knowledge in MS Defender for endpoint and or Cloud.
• Scripting knowledge (Phyton, Regular Expression, Powershell) is desirable;
• Professional Certifications:
• CISSP certified
• Symantec Certified Expert: Administration of Data Loss Prevention (any version)

Next Step

• Prepare your updated resume and expected package.
• Simply click on 'Apply here' or email to [email protected] to drop your resume
• All shortlisted candidates will be contacted.

Tamanna Bilandi

EA Licence No. 91C2918

Personnel Registration No. R2096241

Responsibilities

• Good understanding of concurrent software systems and building them in a way that is scalable, maintainable, and robust
• Experience in designing application solutions in hadoop ecosystem
• Deep understanding of the concepts in Hive, HDFS, yarn, Spark, Spark sql, Scala and Pyspark
  HDFS file formats and their use cases (eg Parquet, ORC, Sequence etc)
• Good knowledge in data warehousing system
• Experienced in any scripting language (SHELL, PYTHON)
• HortonWorks distribution and understanding on SQL engines (Tez, MR)
• Java/RestServices/Maven experience is a value addition
• Control-M development. Monitoring Resource utilization using Grafana Tool
• Good skillset to create automation scripts in Jenkins & knowledge in working on automating builds, test frameworks, app configuration etc
• Experience in implementing scalable applications with fully automated deployment and control using Bitbucket, Jenkins, ADO etc
• Any other ad-hoc duties as assigned by supervisor.

Requirements

• Mandatory: Big Data – Hive, HDFS, Spark, Scala, Pyspark.
• Good to have : Schedulers (Control-M), ETL Tool – Dataiku , Unix/Shell scripting , Knowledge of Integration services of FileIT/MQ and others , CI/CD tools – Jenkins, Jira, ADO Devops – tools suite , Oracle .

Interested applicants, please email your resume to Andre Chua Jing Ming

Email: [email protected]

CEI Reg No: R1989053

EA Licence No: 99C4599

Recruit Express Pte Ltd

Responsibilities

• Good understanding of concurrent software systems and building them in a way that is scalable, maintainable, and robust
• Experience in designing application solutions in hadoop ecosystem
• Deep understanding of the concepts in Hive, HDFS, yarn, Spark, Spark sql, Scala and Pyspark
  HDFS file formats and their use cases (eg Parquet, ORC, Sequence etc)
• Good knowledge in data warehousing system
• Experienced in any scripting language (SHELL, PYTHON)
• HortonWorks distribution and understanding on SQL engines (Tez, MR)
• Java/RestServices/Maven experience is a value addition
• Control-M development. Monitoring Resource utilization using Grafana Tool
• Good skillset to create automation scripts in Jenkins & knowledge in working on automating builds, test frameworks, app configuration etc
• Experience in implementing scalable applications with fully automated deployment and control using Bitbucket, Jenkins, ADO etc
• Any other ad-hoc duties as assigned by supervisor.

Requirements

• Mandatory: Big Data – Hive, HDFS, Spark, Scala, Pyspark.
• Good to have : Schedulers (Control-M), ETL Tool – Dataiku , Unix/Shell scripting , Knowledge of Integration services of FileIT/MQ and others , CI/CD tools – Jenkins, Jira, ADO Devops – tools suite , Oracle .

Interested applicants, please email your resume to Andre Chua Jing Ming

Email: [email protected]

CEI Reg No: R1989053

EA Licence No: 99C4599

Recruit Express Pte Ltd

Zenith Infotech is a Tech Recruitment Company in Singapore for the past 27 years. We are looking for a suitable candidate for the above role

• Perform operation, installation, and monitoring of big data platforms
• Ensure the reliability and normal operation of multiple core systems for big data and online computing, resolving issues within the agreed SLA
• Evaluate infrastructure requirements for deployments and upgrade activities
• Develop and maintain technical documentations related to design, configuration, troubleshooting, backup, DR, etc
• Ensures deployment and operations of the data platform comply with prevailing security, regulations and audit requirements
• Provide recommendations on data governance practices and in-depth optimizations best practices

Requirements:
.DevOps and system engineers in Unix
• Solid computer software basic knowledge; understand Linux operating system, storage, network IO and other related principles
• Familiar with one or more programming languages, such as Python/Go/Java/Shell/Ansible
• Experience with Cloudera, Informatica, or Denodo and its runtime components would be highly advantageous
• Relevant computing/distributed/big data system experience (Hadoop/HDFS /Kubernetes/Docker/OpenStack/Hadoop/Spark/Flink,etc.) would be advantageous
• Good data structure and system design skills highly preferred
• Good knowledge of information security highly preferred

Job Highlights

Salary: $2800 per month

Contract Duration: 11 months

Working Location: Nearest to Labrador Park MRT

Working Hours: Monday to Friday, normal office hours

Job Descriptions

• Design, develop, update and maintain the Data Centre (DC) database and dashboard using
  Tableau.
• Collate operational data from multiple stakeholders and update the DC database.
• Analyse the data/database to uncover trends, patterns, and insights, and generate/update
  dashboards and reports to aid in operational and policy decisions

Job Requirements

• Only Singaporean need to apply.
• Diploma in Computer Science, Data Science, Mathematics, Statistics, Business Analytics or equivalent field.
• Familiar in visualizing data using Tableau.

Interested candidate please click ‘Apply Now’. We regret to inform that only shortlisted candidates will be contacted.

Yee Kar Seng

Outsourcing Team

BGC Group Pte. Ltd.

EA Registration No.: R22107286

EA License Number: 05C3053

Objectives of the Role:

• Act as the primary point of contact for all client concerns and needs related to Data & AI engagements.
• Manage large strategic accounts, exceeding $10M, with a focus on growth and client satisfaction.
• Foster and strengthen long-term partnerships with clients by maintaining effective relationships.
• Collaborate with sales and internal teams to develop strategic solutions, ensuring KPIs and business objectives are met.
• Navigate and thrive in the fast-evolving fields of business and technology.
• Deeply understand the company's products and services to identify upsell and cross-sell opportunities.

Key Responsibilities:

• Serve as the primary contact for inquiries and requests from clients, addressing their data and AI-related needs.
• Ensure that client services align with budgets, expectations, and timelines.
• Regularly engage with internal teams to discuss progress, challenges, and strategies for business improvement.
• Prepare and present progress reports to clients and senior leadership.
• Identify upsell, cross-sell, and renewal opportunities, collaborating closely with the sales team.
• Manage the delivery of solutions using industry-standard project management methods.
• Lead discussions on AI & ML use cases, implementation strategies, and business benefits to drive value for clients.
• Ensure all services delivered are of high quality and align with data governance practices, including data quality, data profiling, data cataloging, and metadata management strategies.

Requirements:

• Bachelor’s Degree in Computer Science or equivalent.
• Atleast 8 years of experience in Data & AI with extensive experience in Data Marts, Data Warehouses, Data Lakes and Data Bricks.
• Strong understanding of current trends in AI and Machine Learning (ML), with the ability to guide discussions on AI & ML use cases and advanced analytics implementations.
• Deep technical knowledge of cloud technologies and cloud data platforms (e.g., Microsoft Azure, Google Vertex AI, Amazon Web Services (AWS)).
• Expertise in Data Governance practices, including the development of solutions for Data Quality, Data Profiling, and Metadata Management.
• Ability to multitask effectively and manage several responsibilities simultaneously.
• Excellent communication skills, both written and verbal, with strong organizational and attention-to-detail abilities.
• Experience drafting Statements of Work (SOWs), Proposals, Master Services Agreements (MSAs), and Service Level Objectives (SLOs).
• Demonstrated success in managing client revenue, profit, and loss while ensuring high-value contract wins.
• Experience serving as a trusted advisor to clients, with the ability to build and maintain senior-level relationships.
• Orchestrates the activities between HCL and Clients at various levels – Executives to Technologists
• Finds opportunities to engage the clients in a structured way by building winning Proposals.
• Proactively creates initiatives to share thought leadership.
• Demonstrated leadership by engaging the organization to deliver industry differentiating solutions.
• Plan for resources with the right skills and knowledge for effective engagement on the accounts.
• Manage assigned human resources by leveraging the hire to retire process.
• Knowledge and experience in managing the entire hire-to-retire process for human resources within an account.

SSG is a dynamic and forward-thinking organization dedicated to empowering individuals and shaping the future of Singapore's workforce. As a statutory board under the Ministry of Education, SSG leads the charge in driving the SkillsFuture movement, a national initiative that promotes lifelong learning and skills development. With a strong focus on innovation and collaboration, SSG works closely with employers, training providers, and individuals to create a vibrant ecosystem of learning and growth. By offering a wide range of initiatives, programs, and funding schemes, SSG enables individuals to unlock their full potential, acquire new competencies, and stay ahead in a rapidly changing job market.

Join the Data Strategy & Analytics Division (DSAD) team to grow SSG into a data-mature organization where we use data pervasively and securely to deliver on our business missions:
• Develop and drive SSG’s data strategy, including LOIs, data competency, and maintaining strong links with CIO Office
• Develop, implement and maintain comprehensive data governance and management framework that complies with WOG requirements Implement Lines of Inquiries
• Support data management and exploitation
• Develop MLOps and instil best practices

What you will be working on

As a Data Engineer within DSAD, you will play a pivotal role in managing and optimizing data pipelines, ensuring the seamless flow and integrity of data across our organization. Your expertise in data pipeline management, automation, MLOps, data governance, and infrastructure architecture will contribute significantly to our mission of leveraging data to drive innovation and operational excellence. We are looking for a candidate who embodies our core values of integrity, collaboration, and continuous improvement, and who is passionate about harnessing the power of data to achieve our strategic objectives.

• Data Pipeline Management, Automation, and MLOps Proficiency
  - Manage and optimize multi-stage data pipelines for various use cases, from data acquisition to consumption
  - Automate data preparation and integration tasks using innovative tools and techniques
  - Apply MLOps principles to integrate machine learning models efficiently with data pipelines and infrastructure
• Data Governance, Cataloging, and Collaboration
  - Work closely with data governance teams to ensure data is accurately cataloged and available for governed reuse
  - Collaborate with AI engineers to optimize data solutions for machine learning projects, focusing on data flow and accessibility
• Infrastructure Architecture and Data Modeling
  - Design and manage scalable data infrastructure using cloud services like AWS
  - Develop efficient data models and pipelines for large-scale data sets, ensuring data quality and availability
• Data Quality Assurance, Documentation, and Continuous Improvement
  - Lead initiatives to establish standards for data accuracy and reliability
  - Maintain comprehensive documentation on data architectures and management practices
  - Stay updated on data engineering advancements, advocating for and implementing improvements
  - Facilitate knowledge sharing and technical training sessions to enhance organizational data competency

What we are looking for

• Tertiary qualifications in computer science, statistics, applied mathematics, data management, information systems, information science, or a related quantitative field
• A minimum of six years of experience in data management disciplines, including data integration, modeling, optimization, and data quality
• At least three years of experience in cross-functional team collaboration and supporting data management/analytics initiatives
• Demonstrated ability to work creatively and collaboratively with both business and IT teams
• Strong interpersonal skills with the ability to engage and earn the respect of stakeholders at all levels
• Confident, energetic self-starter with a commitment to ethics, regulatory compliance, customer service, and business integrity
• Highly adaptable and committed to excellence in a dynamic business environment

Responsibilities

Data Domain Management

• Interpret business workflows and data requirements.
• Conduct data exploration and create entity relationship diagrams.
• Develop data models and manage ETL processes.
• Create and service data pipelines.

Data Platform Operations

• Set up, install, and manage access controls.
• Monitor and maintain data pipelines to ensure quality data outputs.
• Validate data fusion processes for safe use.
• Data Platform Upgrade and Migration:
• Design, develop, and implement robust processes and automation.
• Conduct testing (unit testing, SIT, UAT) and implementation.
• Ensure secure and efficient data fusion, exploitation, and sharing.

Documentation and Administration

• Maintain data dictionaries and workflow processes.
• Report for Data Incident Concierge (DIC) and other documentation.
• Handle paperwork for data administration, including asset management and procurement of tools.

Collaboration and Continuous Improvement

• Collaborate with partners and cross-teams to benchmark best practices.
• Drive continuous improvement in data interpretability and searchability.
• Develop and maintain tools such as Microsoft Purview.

Requirements

• Minimum 4 years of hands-on experience in data engineering, systems implementation, or equivalent roles.
• Experience in data integration, analytics, system integration, and working on data pipelines.
• Knowledge of information management practices, including data lifecycle management, data modeling, and master data management.
• Experience in gathering requirements for data warehouses or similar systems.
• Familiarity with Change Management, Risk Management, and Incident Management.
• Experience supporting relevant Government Projects and understanding Government Data Governance Standards and Regulations (e.g., IM8, PSGA).
• Experience in public health or epidemiology is advantageous.

Technical Skillset

• Proficient in PySpark, SQL, and/or Python.
• Experience with large datasets.
• Proficiency in Microsoft Azure and Power BI is advantageous.
• Agile or other Project Management Methodology certification is a plus.

Job Description:

• Perform operation, installation, and monitoring of big data platforms
• Ensure the reliability and normal operation of multiple core systems for big data and online computing, resolving issues within the agreed SLA
• Evaluate infrastructure requirements for deployments and upgrade activities
• Develop and maintain technical documentations related to design, configuration, troubleshooting, backup, DR, etc
• Ensures deployment and operations of the data platform comply with prevailing security, regulations and audit requirements
• Provide recommendations on data governance practices and in-depth optimizations best practices

Requirements:
primary skillset: DevOps and system engineers in Unix
• Solid computer software basic knowledge; understand Linux operating system, storage, network IO and other related principles
• Familiar with one or more programming languages, such as Python/Go/Java/Shell/Ansible
• Experience with Cloudera, Informatica, or Denodo and its runtime components would be highly advantageous
• Relevant computing/distributed/big data system experience (Hadoop/HDFS /Kubernetes/Docker/OpenStack/Hadoop/Spark/Flink,etc.) would be advantageous
• Good data structure and system design skills highly preferred
• Good knowledge of information security highly preferred

Responsibilities

• Perform operation, installation, and monitoring of big data platforms

• Ensure the reliability and normal operation of multiple core systems for big data and online computing, resolving issues within the agreed SLA

• Evaluate infrastructure requirements for deployments and upgrade activities

• Develop and maintain technical documentations related to design, configuration, troubleshooting, backup, DR, etc

• Ensures deployment and operations of the data platform comply with prevailing regulations and audit requirements

• Provide recommendations on data governance practices and in-depth optimizations best practices

Requirements

• Degree / Diploma in Computer Science or related

• Minimally 4 years of experience in Data Engineering

• Solid computer software basic knowledge; understand Linux operating system, storage, network IO and other related principles Familiar with one or more programming languages, such as Python/Go/Java/Shell/Ansible

• Extensive experience with Cloudera Data Platform and its runtime components

• Relevant computing/distributed/big data system experience (Hadoop/HDFS/Nginx/Kubernetes/Docker/OpenStack/Hadoop/Spark/Flink,etc.)

• Good data structure and system design skills highly preferred

• Good knowledge of information security highly preferred

Licence no: 12C6060

YOUR ROLE:

The Senior Data Engineer will work on acquiring, storing, governing and processing huge sets of structured / unstructured data. You will bring a vision of the big data solutions landscape for choosing optimal architecture components to use for these purposes as well as a set of data engineering skills for implementing enterprise data foundations such as data lake. Finally, you will work closely with other company experts in Data Intelligence, Research, UX Design, Digital Technology and Agile teams to enable intelligence in the digital mesh of our clients and deliver big impact to them.

YOUR RESPONSIBILITIES:

• Design, implement, and maintain robust and scalable data pipelines to ingest, transform, and process structured and unstructured data from various sources.
• Build and manage data warehouses and data lakes, implementing efficient data storage and retrieval mechanisms. Design data models that support business requirements and analytics use cases.
• Leverage cloud platforms (e.g., AWS, Azure, GCP) to design and deploy scalable data infrastructure, optimizing for performance, cost-effectiveness, and reliability.
• Implement data quality checks, validation processes, and data governance frameworks to ensure data accuracy, integrity, and compliance with security standards.
• Continuously monitor and optimize data pipelines and infrastructure to improve processing speed, reduce latency, and enhance overall system performance.
• Work collaboratively with data scientists, analysts, and other stakeholders to understand their data needs, provide technical expertise, and deliver solutions that meet business objectives.
• Support business users by implementing data presentation layer including data visualisation using tools like Tableau, PowerBI etc.
• Stay up-to-date with emerging technologies and industry trends in the big data and data engineering space, evaluating and implementing innovative solutions to improve data processing capabilities.
• Support the definition and optimization of underlying data infrastructure

WHO YOU ARE:

• You hold a Bachelor's, Master's, or Ph.D. degree in IT, Information Management, and/or Computer Science with at least 6 years of experience.
• Good knowledge of the big data technology landscape and concepts related to distributed storage/computing
• Experience with big data frameworks (e.g. Hadoop, Spark) and distributions (Cloudera, Hortonworks, MapR)
• Experience with batch & ETL jobs to ingest and process data from multiple data sources
• Experience with NoSQL databases (e.g. Cassandra, MongoDB, Neo4J, ElasticSearch)
• Experience with querying tools (e.g Hive, Spark SQL, Impala)
• Experience with Power BI
• Experience or willingness to go in real-time stream processing, using solutions such as Kafka, AWS Kinesis, Flume, and/or Spark Streaming
• Experience or willingness to learn about DevOps and DataOps principles (e.g Infrastructure as Code, automating different parts of the data pipeline)
• High-level understanding of Data Science concepts and methodologies (how models are built, trained, and deployed)
• You are passionate about technology and continuous learning comes naturally to you

YOUR ROLE:

The Senior Data Engineer will work on acquiring, storing, governing and processing huge sets of structured / unstructured data. You will bring a vision of the big data solutions landscape for choosing optimal architecture components to use for these purposes as well as a set of data engineering skills for implementing enterprise data foundations such as data lake. Finally, you will work closely with other company experts in Data Intelligence, Research, UX Design, Digital Technology and Agile teams to enable intelligence in the digital mesh of our clients and deliver big impact to them.

YOUR RESPONSIBILITIES:

• Design, implement, and maintain robust and scalable data pipelines to ingest, transform, and process structured and unstructured data from various sources.
• Build and manage data warehouses and data lakes, implementing efficient data storage and retrieval mechanisms. Design data models that support business requirements and analytics use cases.
• Leverage cloud platforms (e.g., AWS, Azure, GCP) to design and deploy scalable data infrastructure, optimizing for performance, cost-effectiveness, and reliability.
• Implement data quality checks, validation processes, and data governance frameworks to ensure data accuracy, integrity, and compliance with security standards.
• Continuously monitor and optimize data pipelines and infrastructure to improve processing speed, reduce latency, and enhance overall system performance.
• Work collaboratively with data scientists, analysts, and other stakeholders to understand their data needs, provide technical expertise, and deliver solutions that meet business objectives.
• Support business users by implementing data presentation layer including data visualisation using tools like Tableau, PowerBI etc.
• Stay up-to-date with emerging technologies and industry trends in the big data and data engineering space, evaluating and implementing innovative solutions to improve data processing capabilities.
• Support the definition and optimization of underlying data infrastructure

WHO YOU ARE:

• You hold a Bachelor's, Master's, or Ph.D. degree in IT, Information Management, and/or Computer Science with at least 6 years of experience.
• Good knowledge of the big data technology landscape and concepts related to distributed storage/computing
• Experience with big data frameworks (e.g. Hadoop, Spark) and distributions (Cloudera, Hortonworks, MapR)
• Experience with batch & ETL jobs to ingest and process data from multiple data sources
• Experience with NoSQL databases (e.g. Cassandra, MongoDB, Neo4J, ElasticSearch)
• Experience with querying tools (e.g Hive, Spark SQL, Impala)
• Experience with Power BI
• Experience or willingness to go in real-time stream processing, using solutions such as Kafka, AWS Kinesis, Flume, and/or Spark Streaming
• Experience or willingness to learn about DevOps and DataOps principles (e.g Infrastructure as Code, automating different parts of the data pipeline)
• High-level understanding of Data Science concepts and methodologies (how models are built, trained, and deployed)
• You are passionate about technology and continuous learning comes naturally to you

COMPANY DESCRIPTION

Beyondsoft International (Singapore) Pte. Ltd. was set up in 2007 and established as the regional headquarters for the Southeast Asia (SEA) and European markets in September 2015. Based on our vision of "Using technology to promote social progress, economic development and become a global customer preferred partner" and our concept of "Beyond your expectations", Beyondsoft is committed to provide our customers in countries along the "Belt and Road" with comprehensive solutions and products and creating commercial value for customers to realizing continuous businesses development.

Our core business includes:

1. IT development services providing customers with IT consulting, software research and development, software and hardware testing, system integration and operation and maintenance, data analysis and other services;
2. New retail solutions and products through intelligent products, helping small and medium-sized enterprises (SMEs) realize the digital transformation of their daily operations;
3. Internet of Things (IoT) platform and solutions comprehensive use of IoT, artificial intelligence, big data, cloud computing and other technologies to provide IoT solutions for intelligent upgrades in cities, parks, buildings and industries, to create a smart future.

For more information, please visit www.beyondsoft.com.

RESPONSIBILITIES

• Work closely with business stakeholders, data engineers and platform team to implement and support data distribution solution.
• Design an optimal onboarding process with clear visibility of the various life cycle of a product.
• Contribute, influence, and validate the design of data distribution solutions to ensure they meet both business and operational needs.
• Perform data access control operations to ensure data ingested and distributed comply with enterprise data governance and data handling standards.
• Lead the dataset registration conversation with business and metadata team to ensure that the dataset are properly registered.
• Document the business requirements clearly.
• Perform user acceptance testing on the data distribution channel and ensure that it meets the requirements.
• Identify opportunities for continuous improvement in assigned area of work.

• Bachelor's degree in computer science, Engineering, or a related field.
• Minimum 4 years of experience in as a platform engineer or software engineer.
• Good understanding of the principles, key controls and processes relating to data management, as well as data integration and data distribution.
• Familiarity with data visualization tool (e.g. Tableau, PowerBI) and data virtualization technology such as Denodo will be advantageous.
• Strong analytical skill with passion in complex problem solving.
• Basic coding skill will be advantageous.
• Excellent written and verbal communication skills.
• Strong interpersonal skill to interact with diverse stakeholders.
• Agile, fast learner and able to adapt to changes.
• Experience with the System Development Life Cycle (SDLC) implementation methodology and/or Agile methodologies like Scrum and Kanban.

Responsibilities

• Translate stakeholders’ requirements into data solutions that meet the desired performance, scalability.
• Lead teams in designing and developing data solutions configurations as per the proposed architecture.
• Recommend approaches for solving development and integration problems within data warehouse and business intelligence solutions.
• Provide strategy direction and design implementation roadmaps.
• Identify and adopt new technologies & methodologies to increase performance, automation, and scalability.
• Support the business development activities; shape and design solution architectures for a proposal.

Requirements

· 8 Years Experience in Data modelling, development and implementation.

· Experience in tools like Snowflake,Pyflink is must.

· Experience in Data Migration: Strategizing, planning, costing, execution, data retention/archival and disposal.

· Expert knowldge in Data Management: Strategy & Execution, Multi-domain. Tools: Informatica MDM, Stibo PIM, Talend Data fabric.

· Experience in Data Governance: Data/Information governance capability Assessment (as-is, to-be), Framework design, models, roadmap & Execution.

Interested candidate please click "APPLY" to begin your job search journey.

We regret to inform that only shortlisted candidates will be notified.

EVO Outsourcing

RCB No. 202233837K

Responsibilities:

· Design, develop, and maintain data warehouse solutions using Oracle Cloud platform with Oracle Analytics Cloud and ODI Marketplace.

· Collaborate with cross-functional teams to gather and analyze business requirements for analytical models and reporting solutions.

· Develop, implement and support data integration processes to extract, transform, and load (ETL) data from various sources into the data warehouse.

· Design and optimize data models to support business analytics and reporting requirements.

· Develop and deploy analytical models using Oracle Analytics Cloud (OAC) to provide insights and drive decision making.

· Perform data analysis and troubleshooting to identify root causes of issues and implement solutions.

· Develop and maintain documentation of data warehouse architecture, processes, and procedures.

· Stay up-to-date on industry trends and best practices in data warehousing, analytics, and cloud technologies.

Requirements:

· Bachelor's Degree in Computer Science / Information Systems, or related field.

· Minimum of 8 years of experience working with Oracle Analytics Cloud (OAC/OBIA/OBIEE) or similar cloud-based analytics platforms.

· Minimum 8 years of experience working with OBIEE/RPD modeling

· Minimum of 8 years of ETL experience ODI/Informatica - ODI Preferred

· Minimum of 4 years of experience building Analytics Visualization using tools like OAC, Power BI, OBIEE, Tableau

· Strong proficiency in Oracle (SQL/PLSQL) and experience with data modeling and database design principles.

· Experience with data integration tools and techniques

· Experience in designing end-to-end implementation involving Data Analysis, Data Cleansing and Data Modelling

· Experience in collaborating Design reviews with the business analysts and business users to create a proof of concept for the reports.

· Experience in handling Finance and SCM data and the related data pipelines.

· Knowledge in Oracle EBS COA, OU, MOAC , multi-currency configurations.

· Knowledge of data warehousing concepts and methodologies, including star schema, snowflake schema, and dimensional modeling.

· Experience developing and deploying analytical models using Oracle Analytics Cloud (OAC) or similar tools.

· Excellent communication and collaboration skills, with the ability to work effectively in a team environment.

· Strong problem-solving skills and attention to detail.

· Oracle certifications in Analytics Cloud or related areas (preferred).

· Experience in Python to develop machine learning models and AI-driven solutions for predictive analytics and process optimization is a plus

Senior Data Engineer

Job Overview:

We are seeking an experienced and highly skilled Senior Data Engineer with full-stack expertise to join our dynamic Data Engineering team. You will play a crucial role in designing, building, and enhancing web-based data applications. This hands-on engineering role will focus on aggregating data from various sources, processing and transforming it, and ensuring it is delivered to internal and external stakeholders. Your work will directly impact the scalability and effectiveness of our data infrastructure and proprietary analytical tools.

Key Responsibilities:

• Translate business needs into robust, scalable web solutions by designing and developing APIs, front-end interfaces, and tools for real-time data ingestion and transformation.
• Leverage a mix of open-source and proprietary big data technologies to improve data reliability, performance, and overall quality.
• Collaborate with internal teams and stakeholders to ensure best practices in data governance and ensure the integrity of data systems during implementation.
• Act as a technical expert on emerging big data technologies, providing insights and recommendations for continuous improvement.
• Work on large-scale commercial software systems and databases, applying your deep knowledge of Business Intelligence, Analytics, and Big Data tools.
• Develop in production environments using Java, Scala, and Spark programming languages.
• Ensure proficiency in SQL, along with scripting expertise in languages such as Python, Shell, etc.
• Work with big data processing frameworks such as MapReduce, Spark, HBase, and NoSQL.
• Apply your expertise in data management technologies to process and analyze large volumes of data efficiently.
• Contribute to both back-end and web UI development, ensuring seamless integration and performance.
• Provide clear, analytical insights and problem-solving solutions to complex challenges.
• Actively participate in a collaborative team environment, efficiently managing multiple tasks and delivering on time.

Requirements:

• A minimum of 7 years of proven experience in software development, specifically in building large-scale commercial software systems and database platforms.
• Must pass technical proficiency assessments as part of the recruitment process.
• Expertise in Business Intelligence, Analytics, and Big Data processes; experience in web, video, mobile, or adtech domains is a strong advantage.
• Proficiency in Java, Scala, and Spark programming languages.
• Strong SQL skills are essential.
• Solid scripting knowledge in languages such as Python, Shell, or similar.
• Experience with big data processing frameworks like MapReduce, Spark, HBase, and NoSQL.
• Expert knowledge of data management technologies and the software engineering tools needed to handle large-scale data processing.
• Background in Web UI, middle-tier, and backend development.
• A strong analytical mindset with the ability to think critically and provide actionable solutions.
• A team player with the ability to handle multiple tasks simultaneously and meet deadlines.
• A degree in Computer Science, Engineering, Statistics, Mathematics, or a related field is required.

Senior Data Engineer

In this role, you can expect to:

● Support the business’s goal of democratisation of data and data products.

● Drive audience and behavioural analytics, as well as key business metrics with associated dashboard and reporting.

● Collaborate in partnership with diverse teams across such as product engineering, data science and business stakeholder teams to successfully deliver business outcomes.

● Work with a mix of cloud infrastructure and open-source technologies to build, scale, and maintain data workloads.

● Work with media industry data practitioners in domains across sales, marketing and advertising, engineering, corporate and ORGANIZATION publications to deliver innovative and game changing data products and use cases.

● Work to design, build and implement data workloads across both high and low volume and velocity of data to support business use cases.

● Implement cloud-based scalable and reliable data pipelines at significant scale.

● Implement reliable and redundant data workloads to provide accurate, easy-to-use and timely data to deliver positive business outcomes.

You should be able to:

● Build and maintain streaming and batch data pipelines

● Build and maintain transactional and analytical data schemas for data lake, data warehouse and data marts.

● Implement Data Analytics and Business Intelligence frameworks to support Enterprise Data needs.

● Adhere to Data Governance policies and implementation from collection to storage and activation of a broad range of data products.

● Utilise data-related languages and frameworks such as Python, Spark, SQL, Hudi, Iceberg.

● Propose Solutions for Data Pipelines, Data Schema and/or Business Intelligence Dashboards and Reports.

● Adhere and have practised Agile Methodology such as Scrum.

● Implement adhering to Master Data Management Best Practices and Principles.

● Understand and Design Data Models following BI Best Practices such as Dimensional Modelling.

It would be great if you had:

● At least 5 years of relevant hands-on experience in cloud-based data engineering, business analyst, or solution architect roles.

● Experience in data-related infrastructure deployments using Terraform Cloud.

● Experience in using Git for version and release management with knowledge in branching strategies.

● Experience in AWS Data and Analytics services such as EMR, Glue, Lambda, Step Functions, Athena, Kinesis, or QuickSight.

● Implementation Experience in Business Intelligence Platforms and Tools such as Tableau, QuickSight.

● Experience in utilising query engines such as Presto on Data Lakes, Data Warehouses and Data Marts.

● Good communication skills for Data and Analytics concepts and methodologies and how they are relevant to your stakeholders.

You Lead the Way. We’ve Got Your Back.

With the right backing, people and businesses have the power to progress in incredible ways. When you join Team Amex, you become part of a global and diverse community of colleagues with an unwavering commitment to back our customers, communities and each other. Here, you’ll learn and grow as we help you create a career journey that’s unique and meaningful to you with benefits, programs, and flexibility that support you personally and professionally.

At American Express, you’ll be recognized for your contributions, leadership, and impact—every colleague has the opportunity to share in the company’s success. Together, we’ll win as a team, striving to uphold our company values and powerful backing promise to provide the world’s best customer experience every day. And we’ll do it with the utmost integrity, and in an environment where everyone is seen, heard and feels like they belong.

Join Team Amex and let's lead the way together.

How will you make an impact in this role?

Decision Science colleagues will serve as a key member of the Credit and Fraud Risk organization. We seek a thought-leader and a problem-solver who can blend business, technical, and industry best practices when it comes to developing the analyses, models, and algorithms that power our customers’ digital experiences.

This critical team is responsible for managing enterprise risks throughout the customer lifecycle, across our consumer and commercial businesses, and across all our global products. We develop industry-first data capabilities, build profitable decision-making frameworks, create machine learning-powered predictive models, and improve customer servicing strategies.

Our Decision Science teams use industry leading modeling and AI practices to predict customer behavior. We develop, deploy and validate predictive models and support the use of models in economic logic to enable profitable decisions across credit, fraud, marketing and servicing optimization engines.

Responsibilities:

• Work with massive amounts of digital data (Web, App, API) and sophisticated tools in an industry leading Big Data environment.
• Build everything from basic reports to advanced machine learning models and algos to drive improvements to our customer’s online and mobile app experiences.
• Work with product owners to revolutionize the product and content design with a data-driven approach
• Collaborate with tech partners to test, implement and deploy modeling solutions to production system.
• Develop insights into customer behavior and introduce new approaches to transform complex behavioral data into actionable information
• Leverage the power of closed loop through Amex network to make decisions more intelligent and relevant
• Innovate with a focus on developing newer and better approaches using big data & machine learning solutions

Qualifications:

• PhDs in a quantitative field (Computer Science, Statistics, Mathematics, Physics, Operation Research and etc.) with hands-on experience leveraging sophisticated analytical and machine learning techniques. PhD degree with practical experiences NLP is a significant plus.
• Expertise in an analytical language (Python, R or the equivalent), and experience with databases (Hive, SQL, or the equivalent). Knowledge of SAS is a plus but not required.
• Deep understanding of machine learning/statistical algorithms such as deep learning and boosting. Experience with data visualization is a plus
• Demonstrated ability to frame business problems into mathematical programming problems, leverage external thinking and tools (from academia and/or other industries) to engineer a solution and deliver business insights.
• Ability to work effectively in a team environment
• Independent thinker who’s organized, has great attention to detail, and can multi-task
• Strong communication skills
• Ability to learn quickly and work independently with sophisticated, unstructured initiatives
• Ability to integrate with cross-functional business partners worldwide
• Proficient in presentation tools, including Excel and PowerPoint
• Minimally 2 years and above of relevant experienceand diverse community of colleagues with an unwavering commitment to back our customers, communities and each other. Here, you’ll learn and grow as we help you create a career journey that’s unique and meaningful to you with benefits, programs, and flexibility that support you personally and professionally.

Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.

About DKatalis

DKatalis is a financial technology company with multiple offices in the APAC region. In our quest to build a better financial world, one of our key goals is to create an ecosystem-linked financial services business. DKatalis is built and backed by experienced and successful entrepreneurs, bankers, and investors in Singapore and Indonesia who have more than 30 years of financial domain experience and are from top-tier schools like Stanford, Cambridge London Business School with more than 30 years of building financial services/banking experience from Bank BTPN, Danamon, Citibank, McKinsey & Co, Northstar, Farallon Capital, and HSBC.

About the role

We are seeking an experienced Senior Data Scientist to lead our data science initiatives and drive innovation in our financial technology products and services. The ideal candidate will have a strong background in machine learning, deep learning, and their applications in the banking and financial services industry.

Key Responsibilities:

• Lead the development and implementation of advanced machine learning models for a variety of projects, including but not limited to:
  • Fraud detection and prevention
  • Anomaly detection in financial transactions
  • Recommendation engines for financial products
  • Risk assessment and management
  • Customer segmentation and personalization
  • Credit scoring and loan approval automation
  • Anti-money laundering (AML) systems
  • Market trend prediction and algorithmic trading
• Develop and implement large language models (LLMs) for applications such as:
  • Automated document processing and information extraction
  • Sentiment analysis of customer feedback and market reports
• Collaborate with cross-functional teams, including engineering, business stakeholders, and data analysts to identify opportunities, define problems, and implement data-driven solutions
• Mentor junior data scientists and provide technical leadership to the data science team
• Design and oversee the end-to-end machine learning pipeline, from data ingestion and preprocessing to model deployment and monitoring in production environments
• Stay current with the latest advancements in AI and machine learning, particularly in the fintech space, and incorporate new techniques into our projects
• Communicate complex technical concepts to both technical and non-technical audiences, including executives and stakeholders

Requirements:

• Degree in Computer Science, Statistics, Applied Mathematics, or a related quantitative field
• 5+ years of experience in applied data science, with a strong focus on the banking and financial services industry
• Proven track record of building and deploying machine learning models into production environments
• Proficiency in Python and the PyData ecosystem (NumPy, pandas, scikit-learn)
• Strong experience with deep learning frameworks such as PyTorch or TensorFlow
• Familiarity with cloud platforms (AWS, GCP, or Azure) and their machine learning services
• Experience with big data technologies (e.g., Spark, Hadoop) and SQL
• Experience with A/B testing and experimental design in a financial context
• Demonstrated ability to work with and process various data types, including structured financial data, unstructured text, and time series data
• Strong understanding of statistical concepts and their applications in finance
• Excellent communication skills, with the ability to present complex ideas to both technical and non-technical audiences
• Experience leading projects and mentoring junior team members

What will make you stand out:

• Experience with LLMs, including fine-tuning and deployment for specific use cases
• Knowledge of MLOps practices and tools for model versioning, deployment, and monitoring
• Relevant open-source projects, blog posts, conference talks, etc

This role offers an exciting opportunity to work at the forefront of financial technology, applying cutting-edge machine learning techniques to solve real-world problems in the banking and financial services industry. The successful candidate will play a crucial role in shaping the future of our products and services, driving innovation, and contributing to the growth of DKatalis.

This role will require him/her to support in the following tasks:

- Work closely as part of the agile product team to design, develop, test and deploy data analytics/scientist products (e.g. interactive dashboards, reports and machine learning models) under the guidance of the DSTA Product Manager.

- Conduct detailed requirements gathering and clarify requirements with the end users, when required, to formulate, translate and refine their business questions into technical and analytical requirements.

- Carry out data audits and technical feasibility assessments.

- Design and develop data analytics/scientist products with the necessary authorisation mechanisms and measures to meet business, user experience, performance and security requirements, using established processes and tools on the Authority’s Enterprise Data Analytics Platform.

- Work closely with relevant technical teams (e.g. Enterprise Data Analytics Platform team, Data Integration team, Database team etc.) during design, development, system integration, testing and deployment, implementing changes if required.

- Perform vulnerability assessments and code quality tests where applicable. Rectify any vulnerability or code quality issues surfaced.

- Conduct User Acceptance Tests based on acceptance criteria in Product Backlog, review feedbacks received and include them in the Product Backlog for prioritisation if applicable.

- Conduct end-user training, handover training and product demonstrations.

- Provide on-site support to troubleshoot any problems and address users’ queries relating to deployed data analytics/scientist products (interactive dashboards, reports and machine learning models).

- Develop and maintain documentations according to the Authority’s Quality Management System (QMS) guidelines (e.g. user guide, design specifications).

- Work with end-users to explore and analyse data for trends and insights relating to user business questions.

- Maintain existing dashboard for additional indicators/charts including raising Service Request (SR) for data extractions.

Qualifications:

Relevant educational credentials in a quantitative discipline (e.g. statistics, computer science, data science/analytics/engineer, or information systems)

As a Data Analytics Engineer, you will work closely with cross-functional teams to understand business requirements, identify data sources, and develop robust data pipelines. Your expertise in data modeling, analysis, and visualization will be crucial in extracting meaningful insights from large datasets.

Responsibilities:

- Collaborate with stakeholders to understand business objectives and translate them into solutions.

- Design and develop data pipelines to extract, transform, and load (ETL) data from various sources.

- Perform exploratory data analysis to identify trends, patterns, and anomalies in the data.

- Develop predictive models and algorithms to solve complex business problems.

- Implement data visualization techniques to present insights in a clear and actionable manner.

- Optimize data storage and retrieval processes for improved efficiency and scalability.

Requirements:

- Proven experience as a data engineer or data analyst, with a focus on building analytical solutions.

- Proficiency in programming languages such as Python, SQL, and R.

- Strong understanding of data modeling techniques and database design principles.

- Experience with data visualization tools such as Tableau, Power BI

- Familiarity with machine learning algorithms and statistical analysis techniques.

- Excellent communication and problem-solving skills.

- Ability to work independently and collaboratively in a fast-paced environment