Job Overview:
We are seeking a skilled and motivated Data Scientist with expertise in Business and Systems Analysis to join our dynamic team. This role will focus on leveraging data to improve business processes, identify strategic opportunities, and optimize system performance within the Infocomm Technology sector.

As a Data Scientist in this role, you will collaborate closely with cross-functional teams to bridge the gap between technical data analysis and business strategy. You will use advanced data techniques, statistical methods, and business acumen to drive decisions and enhance system efficiencies.

Key Responsibilities:

• Analyze complex business processes and identify opportunities for process optimization through data-driven insights.
• Collaborate with stakeholders to define key performance indicators (KPIs) and business goals, translating them into actionable data-driven strategies.
• Develop models to assess and improve system performance, efficiency, and scalability within the Infocomm Technology environment.
• Conduct data analysis to derive actionable insights that influence business strategies, decision-making, and overall system architecture.
• Work with product and development teams to design, implement, and optimize analytics systems and tools that support business needs.
• Identify, analyze, and interpret trends or patterns in large data sets related to system performance, customer behavior, and market trends.
• Provide clear and compelling presentations of findings to both technical and non-technical stakeholders, ensuring alignment with business objectives.
• Actively participate in system design and improvement discussions, ensuring that data and business goals are aligned throughout the project lifecycle.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Programming & Systems Analysis, Science (Computer Science), or a related field.
• Proven experience in data analysis, business systems analysis, or data science within the Infocomm Technology sector.
• Strong understanding of business processes, system analysis, and how data analytics can enhance business performance.
• Proficiency in statistical and data modeling tools (Python, R, SQL, etc.) and business intelligence platforms (Tableau, Power BI, etc.).
• Experience with system design, requirements gathering, and data-driven solution implementation.
• Excellent communication skills with the ability to translate complex technical data into business terms for key stakeholders.
• Strong problem-solving skills and the ability to think strategically while applying analytical techniques.

Responsibility

The holder of the position is mainly responsible for the following areas in coordination with his / her superior:

Design and build the DWH database models (star schema).

Manage the semantic model in Oracle Analytics Cloud to provide a unified view of our organization's data.

Manage application roles and access rights for end users including row level security filters, to protect sensitive data.

Work with ETL specialists, IT business Consulting as well as external vendors to ensure data ingestion and integration into the database model

Collaborate with Business Controlling and business counterparts on new reporting requirements.

Ensure data quality, security and compliance with industry standards and internal guidelines.

Ensure proper documentation of data infrastructure, data models, workflows as well as security concepts in accordance with internal security policies.

Skills

Looking for a Data Engineer more focused on Database modelling, Currently in Oracle environment and going forward with GCP stack.

Proficiency in SQL and data warehousing

Strong understanding of data modelling techniques and hands on experience building database models (star schema).

Expertise with ETL (extract, transform, load) processes. Familiarity with BI tool integration such as Tableau or Looker

Strong analytical thinking, problem-solving capability, and ability to translate business needs into technical specifications.

Customer-oriented with good communication and interpersonal skills.

Key Responsibilities:

• Data Infrastructure Development: Design and build scalable, efficient, and secure data infrastructure to support advanced analytics and reporting systems.
• ETL Pipeline Development: Develop and maintain robust ETL (Extract, Transform, Load) pipelines to process data from various sources, ensuring high-quality, consistent, and accurate data.
• Data Integration: Integrate multiple internal and external data sources, ensuring seamless data flow across platforms.
• Data Modeling: Create and maintain data models and schemas that ensure the efficient storage and retrieval of data.
• Optimization and Performance Tuning: Enhance the performance and scalability of data pipelines, optimizing for speed and reliability.
• Collaboration: Work closely with data scientists, business analysts, and other teams to ensure that data is organized and accessible for analysis, reporting, and machine learning applications.
• Data Governance: Implement data quality control processes to maintain data integrity and consistency.
• Automation: Automate data workflows and systems to ensure efficiency and reduce manual work.
• Troubleshooting and Maintenance: Monitor the health of data systems, diagnose issues, and maintain optimal data system performance.

Qualifications:

• Education: Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field (or equivalent professional experience).
• Experience:2+ years of experience in data engineering, database management, or a similar field.
  Experience working with cloud platforms (AWS, Google Cloud, or Azure).
  Proficiency in relational and NoSQL databases (MySQL, PostgreSQL, MongoDB, Cassandra).
  Solid experience with ETL processes and tools (e.g., Apache Airflow, Talend, or custom-built pipelines).
  

Responsibilities:

• Design, build and operationalize large scale enterprise data solutions and applications using one or more of AWS data and analytics services in combination with 3rd parties – Spark/Python on Glue, Redshift, S3, Athena, RDS-PostgreSQL, Airflow, Lambda, DMS, Code Commit, Code Pipeline, Code build, etc.

• Design and build production ETL data pipelines from ingestion to consumption within a big data architecture, using DMS, DataSync & Glue.

• Understand the existing applications(including on-premise Cloudera Datalake) and infrastructure architecture.

• Analyze, re-architect and re-platform on-premise data warehouses to data platforms on AWS cloud using AWS or 3rd party services.

• Design and implement data engineering, ingestion and curation functions on AWS cloud using AWS native or custom programming.

• Perform detail assessments of current state data platforms and create an appropriate transition path to AWS cloud.

• Collaborate with development, infrastructure and data center teams to define Continuous Integration and Continuous Delivery processes in accordance with industry standards.

• Work on hybrid Datalake.

• Work closely with multiple stakeholders to ensure high standards are maintained.

Mandatory Skill-set

• Bachelors Degree in Computer Science, Information Technology or other relevant fields

• 3-5 years of work experience with ETL, Data Modelling, Data Architecture to build Datalake. Proficient in ETL optimization, designing, coding, and tuning big data processes using Pyspark.

•1-2 yrs of extensive experience in working on AWS platform using core services like AWS Athena, Glue Pyspark, Redshift, RDS-PostgreSQL, S3 & Airflow(for orchestration).

Registration No. / Unique Entity Number: 199801439D

Disclaimer: The company is committed to ensuring the privacy and security of your information. By submitting this form, you consent to the collection, processing, and retention of the information you provide. The data collected (which may include your contact details, educational background, work experience and skills) will be used solely for the purpose of evaluating your qualifications for the position you're applying for. Your data will be stored securely and retained for the duration necessary to fulfill our hiring process. If you are not selected for the position, your data will be kept on file for a limited period in case future opportunities arise. You have the right to access, correct, or delete your data at any time by contacting us at Quess Singapore | A Leading Staffing Services Provider in Singapore (quesscorp.sg)

Responsibility

• The holder of the position is mainly responsible for the following areas in coordination with his / her superior:
• Design and build the DWH database models (star schema).
• Manage the semantic model in Oracle Analytics Cloud to provide a unified view of our organization's data.
• Manage application roles and access rights for end users including row level security filters, to protect sensitive data.
• Work with ETL specialists, IT business Consulting as well as external vendors to ensure data ingestion and integration into the database model
• Collaborate with Business Controlling and business counterparts on new reporting requirements.
• Ensure data quality, security and compliance with industry standards and internal guidelines.
• Ensure proper documentation of data infrastructure, data models, workflows as well as security concepts in accordance with internal security policies.

Skills

• Looking for a Data Engineer more focused on Database modelling, Currently in Oracle environment and going forward with GCP stack.
• Proficiency in SQL and data warehousing
• Strong understanding of data modelling techniques and hands on experience building database models (star schema).
• Expertise with ETL (extract, transform, load) processes. Familiarity with BI tool integration such as Tableau or Looker
• Strong analytical thinking, problem-solving capability, and ability to translate business needs into technical specifications.
• Customer-oriented with good communication and interpersonal skills.

This will be a 1-year renewable contract based in One North.

Responsibilities

• Development and enhancement of dashboarding capabilities for audit, compliance, and service management reporting
• Promote enhancement of IT controls, processes, and security measures
• Implement initiatives and tools to analyse trends and provide oversight on compliance matters
• Improve effectiveness of update, tracking and reporting of compliance status
• Develop IT compliance guides
• Conduct briefing/awareness campaigns on IT compliance requirements, policies, and best practices.
• Coordinate internal and external audits and policy/ compliance-related assessments
• Monitor and report on status and issues
• Perform internal checks to evaluate effectiveness of IT controls
• Provide support to ad-hoc administrative, comms or operational work that may arise

Qualifications/ Qualities:

• Minimum Diploma in information technology, Computer Science, Engineering or a related field
• Minimum 2 years of working experience in Analytic tools (e.g. MS Power BI, Power Automate etc.) for dashboarding, reporting, and compliance monitoring.
• Experience in coordinating workstreams and tasks undertaken by functional teams within IT division and beyond, collating returns and performing reasonable analysis.
• Knowledge in IT audit or IT compliance or IT policy or IT risk management
• Knowledge of Information Security, cybersecurity principles and best practices
• Strong communication skills
• Analytical mindset
• Attention to detail
• Problem-solving abilities
• Team player, working collaboratively with cross-functional teams, auditors, management, and external stakeholders.
• Adaptable and able to work independently

Ethos Search Associates Pte. Ltd.

EA Licence No: 13C6655

EA Reg No: R1988580 Jacky Chong

One North Consulting is currently hiring Data Engineers with about 8+ years of experience as per details given below.

Interested Singapore Citizens / Singapore Permanent Residents can connect on email id - [email protected]

Skills & Responsibilities: -

As Data Engineer, you will focus on managing the Hadoop cluster, implementing data ingestion framework designing data models.

Your primary role will be to implement data lake & transform the data for business use.

• Experience with at least one Cloud Infra provider (Azure/AWS)
• Experience in building data pipelines using batch processing with Apache Spark (Spark SQL, DataSet / Dataframe API) or Hive query language (HQL)
• Knowledge of Big data ETL processing tools
• Write SQL scripts to test ETL results
• Write scripts to regression test the ETL iterations already completed
• Experience with Hive and Hadoop file formats (Avro / Parquet / ORC)
• Basic knowledge of scripting (shell / bash)
• Experience with CI CD tools such as Jenkins, JIRA, Bitbucket, Artifactory, Bamboo and Azure Dev-ops.
• Understanding of DevOps practices using Git version control
• Debug, fine tune and optimize large scale data processing jobs
• Deliver big data solutions based on premise Hadoop or cloud-based systems like AWS.
• Manage Hadoop cluster, participate in scale out planning & implementation.
• Design ingestion layer for structured & unstructured data (text, voice, xml etc)
• Implement specific data model for business & analytics use.
• Deliver ELT solution including data extraction, transformation, cleansing, data integration and data management.
• Augment with new sources of data including internal/external untapped data.
• Contribute to the establishment and maintenance of cloud computing platform and big data services.
• Provide support for analytics tools & environment like RServer etc & debug performance issues.

Competencies :-

• Databases: RDBMS, SQL programming
• ETL and Data Integration Tools: Azure Data Factory (ADF), Microsoft SQL Server Integration Service(SSIS), SAS Data Integration
• Big Data: Hadoop (Hortonworks), Hive, Spark, Sqoop, etc
• Programming and Scripting: Linux/Unix Shell Scripting, Java, Scala, Hive QL
• BI/Dashboarding: SAS Visual Analytics, Qliksense

Working Experience:

• 8+ years (no upper limit) in data engineering and modelling.
• Hands-on in MS SQL. Should be an expert in MS SQL queries and scripting.
• Hands-on experience in testing ETL systems is mandatory
• Hands-on in managing data mapping, data quality and integrity, performance in data processing.
• Develop and implement techniques and analytics applications to transform raw data into meaningful information
• Experience in Agile software development.
• Candidate should be able to create executable scripts for regression testing purposes
• Experience in testing SSIS ETL mappings is good to have
• Visualise, interpret, and report data findings and may create dynamic data reports as well

If interested, please email us your CV to [email protected]

Responsibilities:

• Responsible for design and optimizing of complex SQL queries to generate reports from the data platform.
• Ensure the accuracy, security and reliability of data used in generated reports. Making sure that the data follows local regulations and company policies.
• Support the creation of data visualization tools and dashboards, ensuring they are built on robust and reliable structures within the company's data platform.
• Collaborate with Data Engineers, Data Scientists, and Data Management teams.
• Liaise with business departments to understand their reporting requirements.
• Conduct in-depth analyses to identify trends, patterns and actionable insights.
• Identify automation opportunities and manage departmental automation processes.
• Improve data collection models and ensure the performance of datasets.
• Develop and maintain documentation including data dictionaries and report definitions.
• Carry out any additional tasks assigned by the Supervisor.

Requirements:

• Degree in Statistics, Engineering, Computer Science or equivalent.
• At least 2 years of relevant work experience.
• Knowledge of SQL and programming.
• Experience using Python and PowerApps is an added advantage.

Interested applicants are welcome to submit your resume to [email protected]

EA. R1107675

Agency no. 07C3676

We are looking for a highly skilled Data Engineer to join our team and help build scalable data pipelines and systems. The ideal candidate will have experience in designing, implementing, and optimizing data architectures to enable effective data-driven decision-making. This role involves working with large datasets, building ETL pipelines, integrating data from various sources, and collaborating with cross-functional teams to ensure seamless data operations.

Key Responsibilities:

1. Data Pipeline DevelopmentDesign, build, and maintain scalable and efficient ETL/ELT pipelines to extract, transform, and load data from diverse data sources into data warehouses or data lakes.
   Ensure data pipelines are robust, reliable, and optimized for performance.
   
2. Data Integration & StorageIntegrate structured and unstructured data from various internal and external sources.
   Develop and maintain data storage solutions, including data lakes, data warehouses, and databases.
   Work with both relational databases (SQL Server, PostgreSQL, MySQL) and NoSQL databases (MongoDB, Cassandra, DynamoDB).
   
3. Data Modeling & ArchitectureDesign and implement data models to support analytical and reporting needs.
   Collaborate with data scientists, analysts, and stakeholders to understand data requirements and translate them into scalable solutions.
   Implement best practices in data governance, data quality, and metadata management.
   
4. Data Pipeline Monitoring & OptimizationMonitor and troubleshoot data pipelines to ensure data availability, accuracy, and integrity.
   Optimize existing data systems for performance, scalability, and cost-efficiency.
   Implement error-handling mechanisms and recovery strategies for critical pipelines.
   
5. Collaboration & DocumentationCollaborate with software engineers, DevOps teams, and business stakeholders to support data-related technical issues and infrastructure requirements.
   Document data processes, pipeline configurations, and system designs to maintain a clear understanding of the data ecosystem.
   

Required Skills:

• Programming: Proficiency in Python, Java, or Scala for data pipeline development.
• Data Technologies: Experience with Apache Spark, Hadoop, Kafka, and Flink.
• ETL Tools: Experience with ETL tools like Apache Airflow, Informatica, or Talend.
• Databases: Strong SQL skills and experience with relational databases (PostgreSQL, MySQL, SQL Server) and NoSQL databases (MongoDB, Cassandra).
• Cloud Platforms: Hands-on experience with cloud platforms like AWS (Redshift, S3, Glue), Azure (Data Lake, Synapse), or Google Cloud (BigQuery, Dataflow).
• Data Warehousing: Strong understanding of data warehousing concepts, including dimensional modeling, star/snowflake schema, and data marts.
• Version Control: Proficiency in using Git for source control and versioning.
• Big Data: Experience in working with large datasets and distributed computing frameworks.

Preferred Qualifications:

• Certification in AWS, Azure, or Google Cloud related to data engineering.
• Experience in data streaming technologies like Apache Kafka, AWS Kinesis, or Azure Event Hub.
• Familiarity with DevOps practices and CI/CD pipelines for data infrastructure.
• Knowledge of containerization and orchestration tools like Docker and Kubernetes.
• Strong analytical and problem-solving skills with a keen attention to detail.
• Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.

Educational Qualification:

• Bachelor’s degree in Computer Science, Data Science, Information Technology, or a related field.

Key Responsibilities:

1. Data Pipeline Development:Design, build, and maintain scalable ETL/ELT pipelines to extract, transform, and load data from diverse sources.
   Automate data ingestion and processing workflows.
   
2. Data Architecture and Storage:Develop and optimize data models and databases (e.g., relational, NoSQL, or data lakes).
   Implement and manage cloud-based data storage solutions (e.g., AWS, Azure, Google Cloud).
   
3. Data Integration and Transformation:Integrate data from various structured and unstructured sources, including APIs and third-party systems.
   Ensure data quality, consistency, and accuracy through validation processes.
   
4. Performance and Scalability:Monitor, troubleshoot, and improve the performance of data systems and pipelines.
   Optimize storage and processing costs for large-scale datasets.
   
5. Collaboration and Support:Work closely with data scientists, analysts, and other stakeholders to understand their data needs.
   Provide technical guidance on best practices for data infrastructure.
   
6. Security and Compliance:Implement data governance, security protocols, and access controls.
   Ensure compliance with relevant data privacy regulations (e.g., GDPR, CCPA).
   

Qualifications:

1. Education and Experience:Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
   Proven experience in a data engineering role (2–5 years preferred).
   
2. Technical Skills:Proficiency in programming languages like Python, Scala, or Java.
   Experience with SQL and database management systems (e.g., MySQL, PostgreSQL).
   Hands-on experience with big data frameworks (e.g., Apache Spark, Hadoop).
   Familiarity with cloud platforms (AWS, Azure, GCP) and services like S3, Redshift, BigQuery, or Databricks.
   Knowledge of data integration tools (e.g., Apache Airflow, Kafka, or Glue).
   
3. Other Skills:Strong problem-solving and debugging abilities.
   Excellent communication and teamwork skills.
   Ability to manage multiple projects and deadlines.
   

Preferred Qualifications:

• Experience with machine learning pipelines and MLOps.
• Knowledge of containerization and orchestration (e.g., Docker, Kubernetes).
• Familiarity with CI/CD processes for data workflows.

We are seeking for an individual who is passionate about numbers, data and translating data into actionable insights that can drive decisions. Driven by curiosity and a desire to improve systems, you will be the data champion of Providend Holding Private Limited and its subsidiaries. You will develop data analytics strategies, manage the implementation of data analytics initiatives, while assisting with strategic decisions on data analytics platform. You will take responsibility in managing our databases, consolidating data from siloed systems into a centralized data platform, ensuring data integrity and developing reports.

On daily operational tasks, you will focus on the following areas:

1. Data Cleaning and Preparation: this includes filtering the data, handling missing values, and preparing the dataset for analysis to ensure accuracy and relevance.
2. Data Exploration and Analysis: use statistical tools and techniques to explore and analyse data, identifying patterns, relationships and trends.
3. Data Visualization: create visual representations of data findings through charts, graphs and dashboards to make the data understandable.
4. Reporting:prepare reports and presentations to communicate the insights and findings from the data to stakeholders, which can influence policy and decision-making processes.
5. Collaboration: work with other departments to understand their data needs and help them make informed decisions based on data insights.

To be successful in this position, you will be someone who is/has:

• Bachelor’s degree in data analytics
• Ability to work with stakeholders to assess business requirements and needs, and translate them into non-technical terms
• Ability to analyse existing tools and databases to provide data solution recommendations
• High-level experience in methodologies and processes for managing large-scale databases
• Demonstrated experience in handling large data sets and relational databases
• Working experience of Data ETL is a must
• Proficiency in process mapping tools, databases and ERP systems
• Hands-on knowledge in SQL and Python programming language is a must
• Experienced in handling huge data on Excel/CSV
• Good written and verbal communication skills
• Can-do attitude, good posture, problem solving mindset
• Initiative, drive and exceptional attention to details
• Tenacious and possesses a strong work ethic
• An independent worker, able to work without much guidance
• A strong team player
• Excellent organisational, problem-solving and multi-tasking skills

Desirable Skills:

• Data analytics services on AWS (e.g. Data Firehose, Kinesis, S3 Data Lake, Glue, QuickSight etc.) or Azure (e.g. Data Factory, Stream Analytics, Event Hubs etc.)
• Working experience in financial institutions is a plus

We are seeking an experienced and innovative Data Architect to design, implement, and optimize data solutions that empower business decision-making. The ideal candidate will have a strong background in data architecture, analytics, and visualization tools, with the ability to manage and structure data for enhanced usability and scalability.

Key Responsibilities:

• Design and implement robust data architectures to support business intelligence, analytics, and data-driven decision-making.
• Develop and maintain data models, structures, and pipelines to ensure efficient data integration and accessibility.
• Collaborate with cross-functional teams to understand data requirements and deliver tailored solutions.
• Ensure the security, integrity, and scalability of data systems.
• Evaluate and select data visualization tools and technologies to meet business needs.
• Provide expertise in data governance, quality assurance, and best practices for data management.

Requirements:

• Proven work experience as a Data Architect, Data Scientist, or Data Analyst.
• Hands-on experience with data visualization tools such as Tableau, Power BI, or similar platforms.
• Strong knowledge of data modeling, data integration, and database design.
• Familiarity with big data technologies and cloud-based data solutions (e.g., AWS, Azure, Google Cloud).
• Proficiency in SQL and other data query languages.
• Excellent problem-solving and analytical skills, with attention to detail.

(EA Reg No: 20C0312)

Only shortlisted candidates will be notified

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

About ST Engineering

ST Engineering is a global technology, defence, and engineering group with offices across Asia, Europe, the Middle East, and the U.S., serving customers in more than 100 countries. The Group uses technology and innovation to solve real-world problems and improve lives through its diverse portfolio of businesses across the aerospace, smart city, defence, and public security segments. Headquartered in Singapore, ST Engineering ranks among the largest companies listed on the Singapore Exchange.

Our history spans more than 50 years, and our strategy is underpinned by our core values – Integrity, Value Creation, Courage, Commitment and Compassion. These 5 core values guide every aspect of our business and are embedded in our ST Engineering culture – from the people we hire, to working with each other, to our partners and customers.

About our Line of Business – Mission Software & Services

Our Mission Software & Services business provides leading-edge mission critical command, control, and communications (C3) systems with secured IT infrastructure and managed services. We support our client’s innovation journey through design thinking, analytics, and AI-enabled decision support with our full suite of cloud computing solutions. We provide intelligent, actionable insights and sustainable solutions to our valued partners in diverse industries including defence, government, and commercial sectors.

Together, We Can Make A Significant Impact

We are looking for a highly competent Data Architect to join the team. In this role, you will play a crucial part in designing and optimizing conceptual and logical database models for our customers in the Public Safety & Security sector.

Your responsibilities include designing data infrastructure for our customers to extract and organize data for authorized individuals to access. Your duties include identifying the customer’s internal and external data sources, collaborating with them to determine their data storage and organizational needs and using the information to create and maintain data infrastructure for them.

Be Part of Our Success

• Develop database solutions to store and retrieve company information
• Install and configure information systems to ensure functionality
• Analyze structural requirements for new software and applications
• Migrate data from legacy systems to new solutions
• Design conceptual and logical data models and flowcharts
• Improve system performance by conducting tests, troubleshooting and integrating new elements
• Optimize new and current database systems
• Define security and backup procedures
• Coordinate with the Data Science department to identify future needs and requirements
• Provide operational support

Qualities We Value

• Proven work experience as a Data Architect, Data Scientist, Data Analyst or similar role.
• In-depth understanding of database structure principles
• Experience gathering and analyzing system requirements
• Knowledge of data mining and segmentation techniques
• Expertise in SQL and Oracle
• Proficiency in MS Excel
• Familiarity with data visualization tools (e.g. Tableau, D3.js and R)
• Proven analytical skills
• Problem-solving attitude

Our Commitment That Goes Beyond the Norm

• An environment where you will be working on cutting-edge technologies and architectures.
• Safe space where diverse perspectives are valued, and everyone’s unique contributions are celebrated.
• Meaningful work and projects that make a difference in people’s lives.
• A fun, passionate and collaborative workplace.
• Competitive remuneration and comprehensive benefits.

Must have skillset :

· Proficient in Python, SQL, PL/SQL, and CICD.

· Familiarity with data warehouses such as Snowflake and Oracle.

· Strong analytical and problem-solving skills.

· Good team player and communication skill.

Skillset (Good to have)

· Familiarity with Denodo

Please refer to U3’s Privacy Notice for Job Applicants/Seekers at https://u3infotech.com/privacy-notice-job-applicants/. When you apply, you voluntarily consent to the collection, use and disclosure of your personal data for recruitment/employment and related purposes.

Job Description:

• Design, develop, optimize, and maintain data architecture and pipelines that adhere to ETL principles and business goals.
• Solve complex data problems to deliver insights that help the organization achieve its goals.
• Code in Python with tools like Apache Spark to build a multi-cluster data warehouse.
• Interact with other technology teams to define, prioritize, and ensure smooth deployments for other operational components.
• Advise, consult, mentor, and coach other data and analytics professionals on data standards and practices.
• Foster a culture of sharing, reuse, design for scale stability, and operational efficiency of data and analytical solutions.
• Codify best practices for future reuse in the form of accessible, reusable patterns, templates, and code bases to facilitate data capturing and management.
• Strong experience in mapping attributes, data profiling, data cleansing, and technical data quality etc.
• Strong experience in Ansi SQL and in-depth knowledge with structured, semi-structured & unstructured data.
• Must have good knowledge of data lake and working experience of migration projects in cloud with providers like AWS or Microsoft AZURE or GCP.
• Good to have experience in working with No SQL, Spark SQL using AWS Glue, EMR, and columnar data store.
• Good to understand data security features like data masking, data encryption, role based & fine grain access control mechanisms etc.

Qualifications:

• 3+ years of relevant experience in data engineering/analytics space.
• Expertise in SQL and data analysis and strong hands-on expertise with at least one programming language: Python.
• Strong knowledge in one or more of the following big data tools: Hive, Hadoop Impala, Spark, Kafka.
• Strong expertise in ETL, reporting tools, data governance, data warehousing, and hands-on experience.
• Experience developing solutions for cloud computing services and infrastructure.
• Experience developing and maintaining data warehouses in big data solutions.
• Up to date on industry trends within the analytics space from a data acquisition processing, engineering, and management perspective.
• Experience in agile development.
• Strong people skills, specifically in collaboration and teamwork.
• High level of curiosity, creativity, and problem-solving capabilities.

Requirements and Skills: Data Architect

• A bachelor's degree in computer science, information technology, or a closely related discipline is usually necessary. A master's degree is preferable
• Developed comprehensive architectural plans to meet specific budgetary requirements and project timelines
• Understanding the Enterprise Wide Data-Warehouse developed using FSLDM Model, the databases, technicality in loading & retrieving data.
• Produced monthly & Weekly reports through Automation using ETL,Datan Wrangling & BI tools using Enterprise wide DW.
• Utilized data visualization tools to effectively communicate business insights.
• Identified, analyzed and interpreted trends or patterns in complex data.
• Formulate and maintain Data Governance, framework for Data Ingestion, Data Quality tracking, Meta Data Management, Classifiers and Security across Platform layers and application based on sensitivity of data being stored including Data Lake, EDW and Business Intelligence.
• Designed internal process improvements to automate repetitive tasks,shortening data delivery times
• Core-banking Solution to enhance payment processing using Application programming, Containers & APIs.
• Work with Java & front end developers and support back end processing through API's for Domestic & International Payments.
• Design an enterprise wide Warehouse system using FSLDM and Source Core Banking data for Analytics and Regulatory reporting.

Job Description:

• Design, develop, and optimize machine learning (ML) models and algorithms to address business challenges.
• Collaborate with cross-functional teams to gather requirements, define objectives, and deploy models effectively.
• Train and fine-tune ML models using appropriate algorithms, techniques, and tools.
• Conduct evaluations to assess model performance, applying methods such as cross-validation, hyperparameter tuning, and ensemble learning.
• Work closely with software engineers and DevOps teams to deploy models in production environments.
• Implement APIs and integrate models into existing systems to enable real-time decision-making.
• Monitor deployed models to ensure optimal performance, address anomalies, and resolve issues.
• Continuously refine models and algorithms based on user feedback and performance metrics.
• Perform exploratory data analysis to uncover trends and insights.
• Use statistical methods and visualization techniques to communicate findings to stakeholders.
• Stay updated on advancements in ML and artificial intelligence (AI).
• Evaluate and recommend new tools, libraries, and methodologies to enhance workflows.

Job Requirements:

• At least 8+ years of hands-on experience in designing, developing, and deploying ML models for real-world applications.
• Deep Learning, Machine Learning, and Statistical Analysis
• Familiarity with Large Language Models and Generative AI technologies is a plus.
• Proficiency in Python and ML frameworks.
• Strong understanding of statistical analysis, probability theory, and hypothesis testing.
• Experience with cloud-based ML tools (e.g., AWS, Azure, GCP) and distributed computing frameworks (e.g., Spark) is advantageous.

Job Description:

Key Responsibilities:

• Support day-to-day Business-As-Usual (BAU) operations and data engineering activities for the Enterprise Data Warehouse.
• Design, develop, and maintain scalable data solutions for data storage, transformation, and analytics.
• Collaborate with cross-functional teams to ensure seamless data integration and operational efficiency.
• Troubleshoot and resolve technical issues to maintain system performance and reliability.
• Ensure adherence to best practices and standards for data engineering solutions.

Qualifications and Skills:

• A degree in Computer Science, Information Technology, or a related field.
• Strong hands-on experience in:Oracle PL/SQL
  Informatica PowerCenter
  
• Proficiency in SQL across any Relational Database Management System (RDBMS).
• Experience with Systems Development Life Cycle (SDLC) implementation methodologies and/or Agile frameworks (e.g., Scrum, Kanban).
• Ability to learn quickly, adapt to changing requirements, and work in an agile, fast-paced environment.
• Strong analytical and problem-solving skills with a passion for solving complex issues.
• Excellent teamwork and communication skills to collaborate effectively with technical and non-technical stakeholders.
• Experience with dbt Core or Snowflake is a plus.

The successful candidate will play a critical role in supporting the smooth operation of the Enterprise Data Warehouse while ensuring high-quality data engineering solutions and seamless integration across teams.

· Proven experience as a Data Engineer, with a strong focus on AWS Redshift.

· Expertise in data modeling techniques and best practices.

· Experience with ETL tools and processes.

· Familiarity with data warehousing concepts and tools.

· Proficient in SQL and scripting languages such as Python or Java.

· Experience with other AWS services such as S3, Lambda, and Glue.

· Strong problem-solving skills and attention to detail.

· Excellent communication and collaboration skills to work effectively with team members and stakeholders.

· Certifications in AWS or data engineering (e.g., AWS Certified Big Data, AWS Certified Data Analytics) are a plus.

Job Summary:

We are seeking a skilled and motivated Data Engineer with expertise in Scala, SQL, and Hadoop to join our dynamic team. In this role, you will design, develop, and maintain scalable data pipelines and systems to process large datasets. You will collaborate with cross-functional teams to deliver high-quality solutions for data storage, transformation, and analytics.

Key Responsibilities:

1. Data Pipeline Development

· Design, build, and optimize scalable data pipelines using Scala and Hadoop frameworks.

· Implement ETL processes for ingesting, transforming, and storing data from various sources

2. Data Analysis and Query Optimization

· Write and optimize complex SQL queries for efficient data retrieval and transformation.

· Troubleshoot and resolve performance issues in queries and data workflows.

3. Big Data Ecosystem Management

· Manage Hadoop-based data infrastructure, including HDFS, Hive, and related components.

· Monitor system performance and optimize resource utilization in a distributed environment.

4. Collaboration and Problem Solving

· Work closely with data analysts, data scientists, and business stakeholders to understand requirements and translate them into technical solutions.

· Provide technical guidance and best practices for data engineering within the team.

5. Automation and Monitoring

· Develop scripts and tools to automate repetitive tasks and enhance system monitoring.

· Ensure data quality and consistency through validation and monitoring mechanisms.

6. Documentation and Compliance

· Document technical solutions, workflows, and processes to ensure knowledge sharing and reproducibility.

· Ensure compliance with data governance and security policies.

Skills and Qualifications:

Technical Skills:

· Proficiency in Scala programming and functional programming principles.

· Strong SQL skills, including query optimization and database design.

· Hands-on experience with Hadoop ecosystem tools such as HDFS, Hive, YARN, and MapReduce.

· Familiarity with other big data tools like Spark, Kafka, or Flink is a plus.

• Opportunity to shape and influence the future of data architecture
• 10% travelling required
• Benefit from mobility/relocation opportunities to other countries

about the company
My client is seeking a talented and adaptable Data Architect to join our team. This role will play a pivotal part in shaping and managing the data architecture for our global portfolio, supporting the company’s transformation journey as we migrate towards SAP and implement agile frameworks.

about the job
As a Data Architect, you will work closely with stakeholders across the globe, to design and implement robust data architecture frameworks. This role requires a dynamic individual with strong change management skills who can manage complex environments, juggle multiple projects, and drive business transformation through innovative data solutions.

• Develop data architecture frameworks for specific tech and data products in compliance with company’s global standards, including reference, meta, and master data management procedures.
• Continuously enhance these frameworks to meet evolving business needs while ensuring optimal data accuracy and accessibility.
• Translate complex business requirements into scalable data products, including databases, data warehouses, and data streams.
• Identify key data assets and assess the impact of product choices from a data architecture perspective.
• Ensure compliance of data models in new applications and align architecture decisions with global enterprise data strategies.
• Actively contribute to company’s agile transformation journey, driving the shift towards agile ways of working across multiple projects simultaneously.
• Manage and influence cross-functional teams to foster a culture of agility and adaptability in the organization.
• Coordinate with other Data and Tech Architects to ensure consistency in architecture decisions and alignment across products and markets.
• Participate in transversal initiatives, such as market intelligence and cross-product family projects, to drive enterprise-wide consistency and innovation.
• Advocate for global enterprise data strategies and provide best practices in data architecture to improve business outcomes.
• Bring forward innovative ideas and industry trends to enhance data usage and integration within the organization.

skills and experience required
At least 8 years of experience in data architecture or related fields, with proven expertise in designing and implementing data frameworks in complex environments.

Strong knowledge of agile methodologies, with experience managing change and transforming operational mindsets.

Hands-on experience in building data infrastructure and working with large financial or business datasets.

Broad knowledge of data integration, warehousing, and management tools, with expertise in SAP and BI platforms.

what's an offer
The permanent opportunity for a Data Architect will pay a salary range of $ 12,000 - $ 14,000 plus benefits. This opportunity provides a wider exposure to the inner workings of a global organization and the chance to make a meaningful impact on its overall success.

To apply online please use the 'apply' function, alternatively you can reach me at https://www.linkedin.com/in/Oliviatoh-032330132/. (EA: 94C3609 / R22109942)

We are representing our client in the global technology and engineering space to look for an highly competent Data Architect to join the team. In this role, you will play a crucial part in designing and optimizing conceptual and logical database models.

Responsibilities

• Designing data infrastructure for customers to extract and organize data for authorized individuals to access.
• Identifying the customer’s internal and external data sources, collaborating with them to determine their data storage and organizational needs and using the information to create and maintain data infrastructure for them.
• Develop database solutions to store and retrieve company information
• Install and configure information systems to ensure functionality
• Analyze structural requirements for new software and applications
• Migrate data from legacy systems to new solutions
• Design conceptual and logical data models and flowcharts
• Improve system performance by conducting tests, troubleshooting and integrating new elements
• Optimize new and current database systems
• Define security and backup procedures
• Coordinate with the Data Science department to identify future needs and requirements
• Provide operational support

Requirements

• Proven work experience as a Data Architect, Data Scientist, Data Analyst or similar role.
• In-depth understanding of database structure principles
• Experience gathering and analyzing system requirements
• Knowledge of data mining and segmentation techniques
• Expertise in SQL and Oracle
• Proficiency in MS Excel
• Familiarity with data visualization tools (e.g. Tableau, D3.js and R)
• Proven analytical skills
• Problem-solving attitude

Data scientist roles and responsibilities include:

• Data mining or extracting usable data from valuable data sources
• Using machine learning tools to select features, create and optimize classifiers
• Carrying out the preprocessing of structured and unstructured data
• Enhancing Data Collection procedures to include all relevant information for developing analytic systems
• Processing, cleansing, and validating the integrity of data to be used for analysis
• Analyzing large amounts of information to find patterns and solutions
• Developing prediction systems and machine learning algorithms
• Presenting results in a clear manner
• Propose solutions and strategies to tackle business challenges
• Collaborate with Business and IT teams

Skills:

• Programming Skills – knowledge of statistical programming languages like R, Python and database query languages like SQL, Hive, Pig is desirable. Familiarity with Scala, Java, or C++ is an added advantage.
• Statistics – Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc. Proficiency in statistics is essential for data-driven companies.
• Machine Learning – good knowledge of machine learning methods like k-Nearest Neighbors, Naive Bayes, SVM, Decision Forests.
• Strong Math Skills (Multivariable Calculus and Linear Algebra) - understanding the fundamentals of Multivariable Calculus and Linear Algebra is important as they form the basis of a lot of predictive performance or algorithm optimization techniques.
• Data Wrangling – proficiency in handling imperfections in data is an important aspect of a data scientist job description.
• Experience with Data Visualization Tools like matplotlib, ggplot, d3.js., Tableau that help to visually encode data
• Excellent Communication Skills – it is incredibly important to describe findings to a technical and non-technical audience.
• Strong Software Engineering Background
• Hands-on experience with data science tools
• Problem-solving aptitude
• Analytical mind and great business sense
• Degree in Computer Science, Engineering or relevant field is preferred
• Proven Experience as or Data Scientist

Are you ready to dive into the exciting world of hedge funds? We’re on the hunt for a talented and driven Data Engineer with 3-4 years of experience to become a vital part of our client's team.

In this role, you’ll be the mastermind behind designing, building, and fine-tuning data pipelines and infrastructure that power our cutting-edge quantitative and investment strategies. Think of it as being the architect of our data universe, where every piece you build has a direct impact on high-stakes decision-making.

Key Responsibilities:

1. Data Pipeline Development: Design, develop, and maintain robust and scalable data pipelines to ingest, clean, and transform large volumes of structured and unstructured data from multiple sources.
   Ensure data availability, reliability, and consistency for downstream analytics and modeling.
   
2. Data Integration and Storage: Implement efficient data integration solutions to connect various internal and external data sources.
   Build and optimize data storage systems, including data lakes, warehouses, and real-time streaming platforms.
   
3. Performance Optimization: Monitor and improve the performance of ETL processes and database systems to minimize latency and maximize throughput.
   Ensure high availability and fault tolerance of data infrastructure.
   
4. Collaboration with Teams: Work closely with quantitative analysts, portfolio managers, and data scientists to understand their data requirements and provide tailored solutions.
   Collaborate with IT and DevOps teams to deploy and maintain infrastructure in production environments.
   
5. Data Quality and Governance: Establish and enforce data quality and validation processes to ensure accuracy and completeness.
   Implement data governance practices to maintain compliance with regulatory requirements.
   
6. Technology Exploration: Stay updated with the latest advancements in data engineering technologies and tools.
   Evaluate and recommend new technologies to enhance the fund's data capabilities.
   

Qualifications:

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• Experience: 3-4 years of hands-on experience in data engineering, preferably in the financial services or hedge fund industry.

Technical Skills:

• Proficient in programming languages such as Python, Java, or Scala.
• Strong experience with SQL and database technologies (e.g., PostgreSQL, MySQL, or Snowflake).
• Hands-on experience with big data tools (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, GCP).
• Experience with data pipeline tools such as Apache Airflow, Luigi, or similar frameworks.
• Familiarity with real-time streaming technologies like Kafka or Kinesis.
• Understanding of data modeling, warehousing concepts, and ETL best practices.

Preferred Qualifications:

• Experience in the hedge fund or financial services industry is highly desirable.
• Knowledge of financial datasets and market data providers (e.g., Bloomberg, Refinitiv).
• Familiarity with machine learning workflows and integrating AI/ML models into data pipelines.

If you or anyone within your network is keen to explore the opportunity then do share your resume with [email protected]

Job Overview:
We are seeking a skilled and motivated Data Scientist with expertise in Business and Systems Analysis to join our dynamic team. This role will focus on leveraging data to improve business processes, identify strategic opportunities, and optimize system performance within the Infocomm Technology sector.

As a Data Scientist in this role, you will collaborate closely with cross-functional teams to bridge the gap between technical data analysis and business strategy. You will use advanced data techniques, statistical methods, and business acumen to drive decisions and enhance system efficiencies.

Key Responsibilities:

• Analyze complex business processes and identify opportunities for process optimization through data-driven insights.
• Collaborate with stakeholders to define key performance indicators (KPIs) and business goals, translating them into actionable data-driven strategies.
• Develop models to assess and improve system performance, efficiency, and scalability within the Infocomm Technology environment.
• Conduct data analysis to derive actionable insights that influence business strategies, decision-making, and overall system architecture.
• Work with product and development teams to design, implement, and optimize analytics systems and tools that support business needs.
• Identify, analyze, and interpret trends or patterns in large data sets related to system performance, customer behavior, and market trends.
• Provide clear and compelling presentations of findings to both technical and non-technical stakeholders, ensuring alignment with business objectives.
• Actively participate in system design and improvement discussions, ensuring that data and business goals are aligned throughout the project lifecycle.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Programming & Systems Analysis, Science (Computer Science), or a related field.
• Proven experience in data analysis, business systems analysis, or data science within the Infocomm Technology sector.
• Strong understanding of business processes, system analysis, and how data analytics can enhance business performance.
• Proficiency in statistical and data modeling tools (Python, R, SQL, etc.) and business intelligence platforms (Tableau, Power BI, etc.).
• Experience with system design, requirements gathering, and data-driven solution implementation.
• Excellent communication skills with the ability to translate complex technical data into business terms for key stakeholders.
• Strong problem-solving skills and the ability to think strategically while applying analytical techniques.