Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

YOUR ROLE

Are you passionate about crafting innovative data solutions that drive impactful business decisions? Join our team as a Data Scientist in Big Data and contribute to building cutting-edge platforms that process and analyze vast datasets with efficiency and scalability.

In this role, you will play a key role in:

• Design and Development: Architect and implement robust data pipelines and ETL processes to ensure data quality, accuracy, and integrity.

• Big Data Expertise: Leverage technologies like Apache Spark, Hadoop, and Kafka to process large datasets, optimize pipelines, and deliver high-performance solutions.

• Data Infrastructure: Develop and maintain scalable data warehouse structures, including schema design and indexing strategies, to support evolving business requirements.

• System Scalability: Design and implement highly scalable software architectures that accommodate increasing user loads while ensuring system reliability.

• Data Security: Collaborate with security teams to implement data security measures, ensuring compliance with regulatory standards and maintaining privacy protocols.

• Collaboration and Leadership: Work with cross-functional teams to translate business needs into technical requirements and mentor junior engineers to foster team growth and innovation.

• Automation: Streamline data flow across systems by building automated scheduling and monitoring mechanisms for optimal performance.

YOUR PROFILE

• 1–3 years of hands-on experience in:

Ø Big Data Technologies: Apache Spark, Hadoop, Kafka.

Ø Programming Languages: Python, Scala, Java, SQL, and Shell scripting.

Ø Cloud Technologies: AWS and Kubernetes.

Ø Data Warehousing: Hive, Impala, Sqoop.

• Proven experience designing and maintaining automated, large-scale data pipelines.

• Demonstrated success in system troubleshooting, performance tuning, and distributed system optimization.

Preferred Skills

• Experience with containerization tools like Docker.

• Familiarity with version control systems (e.g., Git) and frameworks like Spring Boot.

• Knowledge of cloud-native solutions and cloud migration best practices.

Core Competencies

• Data Architecture & ETL Development: Expertise in creating efficient data solutions.

• Big Data Leadership: Strong skills in distributed systems and performance tuning.

• Collaboration: Ability to work effectively with diverse teams to deliver business value.

• Continuous Learning: Commitment to staying current with industry trends and innovations.

WHAT YOU’LL LOVE ABOUT WORKING HERE

• We promote Diversity & Inclusion as we believe diversity of thought fuels excellence and innovation.

• In Capgemini, you are the architect of your career growth. We equip people in maximizing their full potential by providing wide array of career growth programs that empower them to get the future they want.

• Capgemini fosters impactful experiences for its people that would aid in bringing out the best in them for them, for the company, and for their clients.

Disclaimer:

Capgemini is an Equal Opportunity Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, national origin gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.

This is a general description of the Duties, Responsibilities, Qualifications required for this position. Physical, mental, sensory, or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity. Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodations do not pose an undue hardship. Capgemini is committed to providing reasonable accommodations during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.

Click the following link for more information on your rights as an Applicant http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law

ABOUT CAPGEMINI

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2023 global revenues of €22.5 billion.

Get the future you want | www.capgemini.com

• Good communication and problem-solving skills
• Candidates with minimum of 2 years? experience, working as DC operator.
• Excellent interpersonal skills
• Dedicated as well as hard working individual with the intercommunication skills to work at all the level of organization.
• Possess an in-depth knowledge of data center infrastructure technology and components for installation.
• Working knowledge of DC M&E for operation.
• Vendor management.
• Extensive knowledge garnered working as a Data Center Operator
• Thorough knowledge of Data Center Operations with strong knowledge of Operations methodology.
• Experience in eye-ball checking of system faults and failures
• Good technical knowledge on Data Centre monitoring tools.
• Strong written and excellent communication skills.
• People ready to work in 12 hour shift patterns.

Job Description: Big Data Support Engineer – Batch Monitoring (Junior Role)

Experience Requirements:

• 1-3 years of IT experience.
• Minimum 1-3 years of hands-on experience with Hadoop and Kubernetes (K8s) ecosystems.
• At least 1-3 years of relevant experience in the banking/financial services industry.

Skills and Qualifications:

• Demonstrable analytical skills with in-depth knowledge of the Big Data ecosystem in a production support environment.
• Hands-on experience with Hadoop toolsets including Hive, Hue, Spark, Kafka, Kudu, Flink, Ozone, and Streaming applications.
• Strong knowledge of SQL, Python, Java, and Unix shell scripting.
• Incident, problem, and service outage management experience is a plus.
• Excellent communication and articulation skills.

Roles and Responsibilities:

1. Batch Monitoring and Operational Support:
   • Provide operational support to ensure the Service Level Indicators (SLI) of applications are met.
   • Troubleshoot and resolve batch issues and identify root causes to minimize SLA impacts.
   • Proactively identify opportunities for preventive maintenance to enhance system reliability.
2. Performance Optimization:
   • Perform administration and optimization to achieve optimal system performance.
   • Conduct reviews of technical and functional solutions from enhancement/project teams to ensure alignment with established standards.
   • Recommend design and operational optimizations for continuous improvement.
3. Collaboration and Stakeholder Communication:
   • Work closely with diverse teams, including tech infrastructure, application services, and business units, to ensure seamless operations.
   • Provide timely updates on status, progress, issues, and resolutions to business stakeholders.
   • Respond promptly to queries raised by various business units.
4. Data Engineering and Pipeline Management:
   • Build and optimize big data pipelines, architectures, and data sets.
   • Support data transformation processes, metadatamanagement, dependency tracking, and workload management.
   • Work on unstructured datasets and perform root cause analysis to identify opportunities for process improvement.
5. Incident Management and Disaster Recovery:
   • Participate in disaster recovery and business continuity exercises.
   • Support software, platform, and database upgrades for systems.
6. Kubernetes and Streaming Applications Support:
   • Provide support for data APIs and data science/machine learning applications running on Kubernetes platforms.
   • Troubleshoot core Java, Python, and Scala Spark batch, API, and streaming applications.

Preferred Experience:

• Experience with message queuing, stream processing, and scalable big data stores.
• Exposure to ledger balance reporting and GL datareconciliation between systems, datamarts, and reports.
• Knowledge of Teradata FSLDM and performance tuning on MPP data pipelines (e.g., Teradata).

This position is ideal for candidates with a strong foundation in BigData support and batch monitoring, excellent problem-solving skills, and the ability to collaborate effectively in dynamic environments, particularly within the banking/financial services industry

Prudential’s purpose is to be partners for every life and protectors for every future. Our purpose encourages everything we do by creating a culture in which diversity is celebrated and inclusion assured, for our people, customers, and partners. We provide a platform for our people to do their best work and make an impact to the business, and we support our people’s career ambitions. We pledge to make Prudential a place where you can Connect, Grow, and Succeed.

In this role, you will be responsible developing, implementing, and maintaining data governance frameworks and risk management strategies to ensure the integrity, confidentiality, and availability of our organization's data assets. This role requires understanding of data governance principles, risk management methodologies, and regulatory compliance requirements.

Data Governance Framework Development:

• Develop and implement data governance policies, standards, and procedures to ensure data quality, consistency, and security.
• Establish data governance frameworks and best practices to manage data assets effectively.
• Collaborate with cross-functional teams to define data ownership, stewardship, and accountability.

Risk Management:

• Identify, assess, and prioritize data-related risks and develop mitigation strategies.
• Conduct risk assessments and impact analyses to evaluate potential threats to data integrity and security.
• Monitor and report on data governance and risk management activities to senior management.

Regulatory Compliance:

• Ensure compliance with relevant data protection regulations, such as PDPA, GDPR, and other industry-specific standards.
• Develop and maintain documentation to demonstrate compliance with regulatory requirements.
• Stay up-to-date with changes in data protection laws and regulations and update policies accordingly.
• Provide advises on data related incidents and escalations as necessary

Data Quality Management:

• Implement data quality management processes to ensure the accuracy, completeness, and reliability of data.
• Develop and maintain data quality metrics and dashboards to monitor data quality performance.
• Collaborate with data owners and stewards to resolve data quality issues and implement corrective actions.

Training and Awareness:

• Develop and deliver training programs to educate employees on data governance and risk management principles.
• Promote a culture of data governance and risk awareness across the organization.
• Provide guidance and support to data owners and stewards on data governance best practices.

Stakeholder Engagement:

• Work closely with business units, IT, legal, and compliance teams to ensure alignment on data governance and risk management objectives.
• Facilitate data governance committees and working groups to drive data governance initiatives.
• Act as a liaison between business and technical teams to address data governance and risk management concerns.

Who we are looking for:

Competencies & Personal Traits

• Driven and Self-initiated individual
• Strong stakeholder management
• Strong communication skills, ability to storyline and engage in focused discussions
• When empowered, not afraid to make decisions
• Operates effectively even when things are not completely certain

Working Experience

• 4-8 years’ working experience
• Relevant experience in Consulting relating to data management or across multiple business disciplines as data governance professionals, business process engineers or business reporting functions
• Experience in working in a diverse organisation and across front to back business processes

Professional Qualifications

• Knowledge of tools and techniques of data governance
• Knowledge of tools, techniques and processes for gathering and reporting data

Education

• Degree holder of any business/ financial related discipline

Prudential is an equal opportunity employer. We provide equality of opportunity of benefits for all who apply and who perform work for our organisation irrespective of sex, race, age, ethnic origin, educational, social and cultural background, marital status, pregnancy and maternity, religion or belief, disability or part-time / fixed-term work, or any other status protected by applicable law. We encourage the same standards from our recruitment and third-party suppliers taking into account the context of grade, job and location. We also allow for reasonable adjustments to support people with individual physical or mental health requirements.

NYC based company has an entry level position available with our economic data group in our Singapore office located in the Central Business District. We are seeking an energetic candidate with an economics degree to join our growing team of data manager professionals.

Entry level candidates are encouraged to apply. We are looking for candidates who are detail oriented and have good computer and communication skills.

The position includes tracking and research of time-sensitive economic and financial time series from sources to update our databases, running quality assurance checks and researching output, organizing and adding new surveys, and providing client support of our data content and proprietary software.

Positions are available focusing on Asian country macroeconomic and financial data with a monthly starting salary range of S$4.3K to 4.7K. Hours are from 7:30am to 5pm. Fluency in Korean is required as well as English in order to liaise with Asian language speaking associates, clients and data sources.

We are working in a flexible, hybrid environment of 3 days per week in-person at our office. All employees need to be fully vaccinated. You will need a computer with good internet connectivity at home.

This is an excellent opportunity to learn about important economic and financial indicators that the community of economists, strategists and risk managers within the corporate marketplace and public sector rely on.

Please visit http://www.haver.com to learn more about us.

Requirements:
* Submit cover letter and resume
* Have an undergraduate or graduate degree in economics that states your degree classification
* Live within commuting distance
* Be detail oriented and have good computer and communication skills
* Fluency in Korean is required as well as English in order to liaise with Asian language speaking associates, clients and data sources. Japanese and Chinese are also helpful.

Benefits:
* Review and salary raise every 6 months in the first year
* Annual performance-related bonus starts 2nd year

Are you driven and ambitious? ‼️

If so, we want you to be on our team as a Sales and Marketing Superstar!

The Amazon Web Services Professional Services (AWS ProServe) ASEAN organization is looking for an experienced and motivated business-oriented Data practitioner who possess a unique balance of business knowledge and Technology depth in Data and Analytics with hands on keyboard delivery implementation experience in the cloud. AWS ProServe engage in a wide variety of projects for customers and partners, providing collective AWS customer experience, best practices, and technical skills for the Customer. Our team collaborates across the entire AWS organization to bring access to product, service, and training teams, to deliver the right solutions and drive feature innovations for our customers across all industries. This role will focus on advising customers looking to enhance their business or operational outcomes through the use of Data and Analytics on AWS. In this role you will advise on architecture best practices, lead projects, manage customers stakeholders and conduct customer workshops and implement complex Data workloads with our customers and partners.

Key job responsibilities

-Advise customer’s technologists and business leads; help them to explore the art of the possible with Data and Analytics, and to develop scalable Data solutions on AWS to deliver business value in the most effective way. -Discuss complex industry-specific business concepts with customer technologists and business leads especially in FSI, Telco and Retail. -Drive and deliver large, complex customer engagements across pre-sales and delivery from ideation, through architecture design and scoping, all the way to development, testing and roll out. -Conduct workshop sessions to identify opportunities with our customers to scope how they could deliver business value through the use of Data and Analytics on AWS. -Provide technical leadership and excellence on customer engagements to ensure alignment on scope, deliverables, timeline and customer expected outcomes.

About the team

Diverse Experiences

AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS?

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture

Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth

We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Basic qualifications

- Bachelor's Degree or equivalent experience in STEM.

- 5+ years of experience with direct customer (internal or external) interaction with responsibilities in Data and Analytics solutions design, architecture and implementation (Data Lake, Data Warehouse, Lake House, Data Mesh, Data as a Product and Data Governance including Data quality and controls, etc..).

- Ability to think strategically about business, solutions and technical challenges.

- A minimum of 3 years working experience in ASEAN region, and ability to travel to customer locations in ASEAN as needed for pre-sales and delivery activities.

Preferred qualifications

- 3+ years Technical experience preferred, knowledge of Data Technology stack of AWS and integration with Machine Learning and Generative AI - Industry experience with key vertical markets such as Financial Sector, Telecom, and Retail.

- AWS Experience and Certifications, including implementation of cloud-based Data and Analytics solutions.

- Ability to understand and educate customers on cloud computing technologies and workload transition challenges.

- Advanced degree desired (e.g., MBA, MS)

Flexible Services from Pinsent Masons Vario provides legal professionals access to high-quality legal work with top-tier clients.

Our growing hub of legal experts have a variety of skills, specialisms and experience but they all enjoy quality legal projects best suited to their skillset and unparalleled support during their assignments.

We are now looking to expand our bench with an exceptional legal professional with experience in data privacy law.

As a legal consultant, you will need:

• Minimum 8 PQE in-house or within a law firm
• Experience in providing subject legal advice relating to the entire life cycle of personal data from collection to deletion
• Ability to liaise and collaborating on privacy legal matters with, particularly understanding global positions derived from the GDPR and advising when local APAC legal considerations apply
• Experience in online technology and AI is preferred

To join our hub, you need to demonstrate the following:

• Qualified lawyer with a strong academic background
• Top international law firm or equivalent in-house/secondment experience
• Flexible, communicative and adaptable
• Enthusiastic about embracing new work cultures
• Rapidly develop close, trusting relationships

To Apply, click on “Apply” and attach your latest CV. Alternatively you can contact our Account Executive, Rachel Lee at [email protected] for a confidential conversation.

We are seeking a talented and a motivated Senior Data Engineer to join our dynamic team. As a Senior Data Engineer, you will be responsible for designing, implementing, and maintaining scalable data pipelines and infrastructure to support our data-driven initiatives. You will collaborate closely with cross-functional teams to understand data requirements, optimize data models, and ensure the reliability and performance of our data systems.

Key Responsibilities:

 Design, develop, and maintain robust data pipelines to ingest, process, and transform large volumes of structured and unstructured data from various sources (e.g., Database, API, SFTP).

 Build and optimize data models and schemas to support efficient data storage, retrieval, and analysis.

 Implement data integration solutions to consolidate data from disparate systems and sources.

 Work closely with Data Scientists and Analysts to understand their requirements and provide them with clean, reliable, and well-structured data.

 Collaborate with DevOps and Infrastructure teams to deploy and manage data infrastructure in cloud environments (e.g., AWS, Azure).

 Familiar with the concept of data security to ensure the data pipelines are secured and PII (Personally Identifiable Information) data are encrypted.

 Monitor and optimize the performance, scalability, and reliability of data systems to ensure high availability and low latency.

 Design and develop MLOps production pipelines; provide technical support to data scientists/ML engineers by getting their ML/DL models deployed at scale and meeting SLAs on both cloud and on-premises GPU and CPU instances.

 Develop and maintain documentation, standards, and best practices for data engineering processes and technologies.

 Stay current with emerging technologies and trends in data engineering and contribute to the continuous improvement of our data architecture and practices.

 Explore, evaluate, and champion the introduction of next-generation technologies in the data-ingestion workflow. Participate in project planning and provide technical guidance on cloud architecture for data projects.

Requirements:

 BS in Computer Science or other related discipline is required. Advanced degrees in Computer Science (PhD, MS) are highly desirable.

 Proven experience (3 years) working as a Data Engineer or in a similar role.

 Strong proficiency in programming languages such as Python. Conversant with data structures and algorithm design.

 Hands-on experience with distributed computing frameworks and big data technologies such as Spark, Kafka, etc.

 Proficiency in SQL and experience with relational databases (e.g., Azure SQL DB, AWS Redshift).

 Experience with data modelling, ETL/ELT processes, and data warehousing concepts.

 Familiarity with cloud platforms and services (e.g., AWS S3, AWS Step Functions, AWS Airflow, Azure Data Logic Apps, Azure Blob Storage).

 Experience with setting up SSO using AD and implementing RBAC (Role Based Access Control) for data security.

 Excellent problem-solving skills and attention to detail.

 Effective communication and collaboration skills, with the ability to work effectively in a cross-functional team environment.

 Experience with version control systems (e.g., Git) and CI/CD pipelines is a plus.

Overview / Brief

Louis Dreyfus Company is a leading merchant and processor of agricultural goods. Our activities span the entire value chain from farm to fork, across a broad range of business lines, we leverage our global reach and extensive asset network to serve our customers and consumers around the world. Structured as a matrix organization of six geographical regions and ten platforms, Louis Dreyfus Company is active in over 100 countries and employs approximately 18,000 people globally.

We are looking for a highly skilled Data Scientist for our global Weather Desk with a strong background in Meteorology. The ideal candidate will hold a PhD or Master’s degree in Atmospheric Science or a related field. We seek for someone who is passionate not only about data analytics and modeling, but also enjoys interpreting large-scale weather patterns and teleconnections. The role balances forecasting work for commercial teams and research projects using data science. The ideal candidate is proficient in weather forecasting and understands the driving forces behind expected weather patterns.

Diversity & Inclusion

LDC is driven by a set of shared values and high ethical standards

Diversity is part of our DNA. LDC strives to create a diverse and inclusive work environment where people can thrive regardless of gender, sexuality, ethnicity or background.

Sustainability

Sustainable value is at the heart of our purpose as a company

We are passionate about creating fair and sustainable value, both for our business and for other value chain stakeholders: our people, our business partners, the communities we touch and the environment around us.

Main Responsibilities:

• Lead global weather intelligence and monitoring for the SouthEast Asia regional commercial offices
• Conduct research, perform data analysis, and create predictive models using meteorological datasets
• Work with internal team to expand and improve suite of weather monitoring tools and visualizations
• Collaborate with cross-functional teams to translate complex weather/climate data into actionable insights through an agricultural commodity lens
• Present weather and research output to both technical and non-technical stakeholders on a regular basis
• Interact with our AI Hub in Singapore and ensure LDC benefits from the most recent developments in weather-related AI

Experiences:

• At least 1-3 years of relevant experiences
• Strong background in meteorology and forecasting
• Proven experience in research and data analytics
• Experience with agricultural commodities and trading is a plus
• Experience with modeling techniques and machine learning algorithms is a plus
• Experience with Google Earth Engine is a plus
• Genuine interest in commodity trading industry
• Strong analytical and statistical capabilities, with a proven track record in problem-solving
• Excellent communication skills
• Ability to work independently and in collaborative settings

Technical Skills:

• Proficiency in Python
• Experience in data analysis libraries (e.g. Pandas, NumPy, SciPy)

Academics:

• PhD or Master’s in Atmospheric Science, Agricultural Science, Meteorology or related field of study

Our client is actively searching for a Data Analyst/ Senior Data Analyst to join their team!
If you are a dynamic individual seeking a new career opportunity, read further!

As a Data Analyst/Engineer, you will be responsible for creating user-friendly applications that will be able to launch Machine Learning (ML) models and trigger automation solutions. You will need to work closely with cross-functional team of data scientists, engineers, business stakeholders and IT team to support patient care and improve health services delivery.

The responsibilities of this role are:

• Lead in the gathering of requirements by working and coordinating with clinicians and business stakeholders.
• Translate business requirements into system and architecture design of applications.
• Work with cross-functional teams to successfully develop and deploy automation solutions (including ML Model), ensuring timelines and quality standards are met.
• Work with the IT/data management team to design, architect and maintain the required data inflow and outflow.
• Liaise with analytics platform and clinical system custodians for model deployment and workflow integration.
• Communicate effectively with stakeholders about progress, challenges, and outcomes, translating complex technical concepts into understandable terms.
• Drive continuous improvement model performance and facilitating adoption.
• Create and maintain proper project documentations.
• Perform de-identification and encryption for department managed datasets according to data management guideline.
• Take accountability in considering compliance to policies, guidelines and regulations and take appropriate steps to mitigate the risks.
• Provide prompt feedback to supervisor in anticipation of work-related problems.
• Perform general administrative duties as required.
• Carry out any other duties or responsibilities assigned by the Supervisor and/or the Head of Department.

The ideal candidate will need to have the following qualities and experience:

• Minimum Bachelor's degree in Computer Engineering, Software Engineering or equivalent with at least two (2) years of experience.
• Proficient in programming languages such as Python (e.g., Flask, Django), R (e.g., Shiny), SQL.
• Experience in managing AI/ML products is highly desirable.
• Experience in SharePoint, Excel (Visual Basic), HTML, XML, Java preferred.
• Knowledge in Data anonymization, de-identification and re-identification process and techniques is preferred.
• Possess skills in statistical modeling and machine learning with experience in data storage, processing, analytics and distribution software and platforms.
• Strong communication/people skills required to interact with data scientists, engineers, business end-users and vendors to design and develop solutions.
• Ability to write clear documentation of procedures, and ability to write specifications for data models to be developed.
• Participate actively as a team member in organizational development and quality improvement.
• Be a change agent and inculcate mindset for change for hospital-wide and departmental- level.
• Able to work beyond routine work responsibilities and office hours, in the exigencies of services e.g., during infectious disease outbreaks.

An exciting career awaits the right candidate! Click "Quick Apply" to register your interest now.

All applicants' CV will be treated with the strictest confidentiality. We regret to inform that only shortlisted candidates will be contacted.

Job Description

The candidate should possess the following: At least (2) years of hands-on experience as Azure Data Engineer using:

Azure Data Factory Azure Synapse Analytics / Datawarehouse

Preferably with relevant certifications from Microsoft including Azure Data Engineer Associate

At least (3) years of hands-on experience in

- Performing data Ingestion using Data factory T-SQL stored procedure and data harmonizing

- Implementing Data Quality validation

- At least (3) years of hands-on experience in

- Providing technical support (80%) enhancements (20%) for existing applications in Azure

(Team has several ongoing projects on the Azure platform, including Finance, Commercials, and Operations. This role requires a support engineer primarily focused on existing projects and understanding the teams dynamics. The role requires someone capable of directly addressing system issues and resolving them. Users report issues, such as error messages and screenshots etc. The data engineer needs to log into the production system, trace processes end-to-end, identify the root cause, and resolve the problem. The engineer is expected to verify the accuracy of data and processes, ensuring correct numbers and outputs.)

Good to have following skills

Knowledge of Azure Databricks

Data modelling in Azure Analysis Services using star and snowflake schema.

Knowledge of writing DAX query to create measures dimensions.

Python Coding Experience

Non-Technical Skills Requirements (Business Skills) At least (3) years of relevant experience in:

Business Requirement Analysis.

EA Number: 11C4879

We are seeking a highly skilled Market Data Analyst Presales Engineer to join our dynamic team. In this role, you will play a pivotal role in driving sales by leveraging your deep understanding of market data and technical expertise. You will collaborate closely with the sales team to identify and qualify opportunities, conduct in-depth technical assessments, and deliver compelling product demonstrations.

Technical Expertise:

Develop a strong understanding of our products and services (Cryptocurrency, Investments, etc), including their technical specifications, capabilities, and benefits.

Stay up-to-date with industry trends, emerging technologies, and competitive landscapes.

Conduct in-depth technical assessments of client requirements and propose tailored solutions.

Contribute to the development of the investment strategy, focusing on emerging trends in Fintech and infrastructure.

Identify new areas for investment within the fintech space, particularly in Payment solutions and decentralized technologies.

Presales Support:

Collaborate with the sales team to identify potential opportunities and qualify leads.

Develop and deliver compelling product demonstrations, presentations, and technical proposals.

Address technical questions and concerns from prospective clients, providing clear and concise explanations.

Conduct proof-of-concept (POC) implementations and data analysis to showcase the value of our solutions.

Data Analysis and Insights:

Analyze market data to identify trends, opportunities, and potential challenges.

Leverage data analysis techniques to support sales efforts and provide valuable insights to clients.

Develop custom data analysis solutions to address specific client needs.

Required Skills:

Data Analysis, Market research, Presales

domain Skills:

Cryptocurrency, Investments, etc.

Portfolio management experience is preferred.

About Us
We are living in dynamic times. Technology is reshaping how we live, and we want to use it to redefine how financial services are offered. This is why we are coming together to unlock big dreams, and financial inclusion for people in our region is just one of them. We want to build a digital bank with the right foundation - using data, technology and trust to solve problems and serve customers.

We're seeking a driven and skilled Credit Risk Data Scientist to join our dynamic team. If you're passionate about predictive modelling, risk management, and leveraging cutting-edge technologies, this role offers an exciting opportunity to contribute in two key areas:

Credit Risk Models:

• Develop, maintain, and monitor predictive models for credit scoring, fraud detection, and suspicious activity prediction.
• Write high-quality, production-ready code for models to be deployed in the production environment.
• Deploy models in the MLOps production environment, maintaining and troubleshooting any issues.
• Support regular model performance reviews, audits, and recalibrations.
• Leverage alternative data sources to enhance underwriting and credit risk models.
• Ensure alignment with model governance, business, and regulatory expectations.

Data Analytics to Help Business:

• Collect, process, and analyze data to support statistical analysis and risk decision-making.
• Design, implement, and maintain performance reports and actionable insights dashboards.
• Provide data-driven insights and develop dashboards to support loan approval processes and business decision-making.
• Conduct in-depth analyses to identify trends, patterns, and anomalies in lending data that can influence credit risk strategies.
• Present model concepts and metrics to senior stakeholders and validators/auditors.

Experience and Qualifications

• Degree (PhD, Master's, Bachelor's) in Statistics, Mathematics, Economics, Finance, Risk Management, or related field.
• Proven experience building risk models such as Application Score, Behavior Score, PD, EAD, LGD (Basel or IFRS 9), especially for retail customers in diverse countries including Singapore.
• Comprehensive understanding of risk management throughout the customer journey within fintech or risk-focused environments.
• Domain expertise in retail credit products, banking, and regulatory frameworks (Basel, IFRS).
• Proficiency in Python, R, SQL, Snowflake and Data Visualization tools like Tableau.
• Technical proficiency in data retrieval, data modeling, data mining, and predictive modeling.
• Strong familiarity with advanced machine learning techniques, statistical classification/regression for credit risk.
• Exceptional problem-solving skills, detail-oriented mindset, and ability to thrive in a dynamic work setting.
• Bonus: Familiarity with implementing models using Terraform scripts, Docker/Kubernetes, CI/CD technologies, AWS, or MLOps.

Description

• Design, develop, and maintain scalable data pipelines using Spark and Scala to process large datasets.

• Implement and manage Elasticsearch clusters for efficient data retrieval and analysis.

• Collaborate with data scientists and analysts to understand data requirements and provide support for analytical solutions.

• Utilize Quantexa for entity resolution and network analytics to enhance data quality and insights.

• Monitor and optimize data workflows for performance, reliability, and scalability.

• Document data processes and ensure best practices in data engineering are followed.

• Participate in code reviews and contribute to the continuous improvement of our data engineering practices.

Requirements

• Proven experience as a Data Engineer, with a strong focus on Spark and Scala.

• Proficiency in Elasticsearch for search and analytics applications.

• Familiarity with Quantexa or similar tools for data enrichment and entity resolution.

• Experience with cloud platforms (AWS, Azure, GCP) is a plus.

• Strong SQL skills and experience with relational databases.

As a highly collaborative organization, our data engineers work cross-functionally with software engineering, data science, and product management to optimize growth, strategy, and experience for our 3 billion plus users, as well as our internal employee community. In this role, you will see a direct correlation between your work, company growth, and user satisfaction. Beyond this, you will work with some of the brightest minds in the industry, and you'll have a unique opportunity to solve some of the most interesting data challenges with efficiency and integrity, at a scale few companies can match.

RESPONSIBILITIES

• Manage and execute data warehouse plans for a product or a group of products to solve well-scoped problems
• Identify the data needed for a business problem and implement logging required to ensure availability of data, while working with data infrastructure to triage issues and resolve
• Collaborate with engineers, product managers and data scientists to understand data needs, representing key data insights in a meaningful way
• Build data expertise and leverage data controls to ensure privacy, security, compliance, data quality, and operations for allocated areas of ownership
• Design, build and launch new data models and visualizations in production, leveraging common development toolkits
• Independently design, build and launch new data extraction, transformation and loading processes in production, mentoring others around efficient queries
• Support existing processes running in production and implement optimized solutions with limited guidance
• Define and manage SLA for data sets in allocated areas of ownership

MINIMUM QUALIFICATIONS

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• 2+ years of work experience in data engineering
• Experience with SQL, ETL, data modeling, and at least one programming language (e.g., Python, C++, C#, Scala, etc.)

PREFERRED QUALIFICATIONS

• Experience with one or more of the following: data processing automation, data quality, data warehousing, data governance, business intelligence, data visualization, data privacy
• Experience working with terabyte to petabyte scale data

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.

Job Summary:

An exciting opportunity for Data Engineer to be a part of a project for strategic initiatives in architecting, designing and building next-generation cloud-based data platforms.

Mandatory Skill-set:

• Degree in Data Engineering, Computer Science, Information Technology;
• At least 5 years of experience in data engineering and modelling;
• Strong hands-on exposure in data science, data analytics and / or data engineering;
• Deep understanding of system design, data structure and algorithms, data modelling, data access, and data storage;
• Have experience with Big Data platforms such as Hadoop, Spark, and NoSQL databases;
• Advanced SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases;
• Good understanding in using cloud technologies such as AWS, Azure, and Google Cloud;
• Experience with orchestration frameworks such as Azure Data Factory, Airflow;
• Proficiency in programming languages such as Python, R, Java, or Scala;
• Familiarity with building and using CI/CD pipelines;
• Familiarity with DevOps tools such as Git, Terraform, Git;
• Strong hands-on exposure with ETL Extract, Transform, Load tools;
• Possess strong written and verbal communication abilities, effectively conveying information to various stakeholders.

Desired Skill-set:

• Experience in designing, building, and maintaining batch and real-time data pipelines;
• Experience with Databricks or Snowflake.

Responsibilities:

• Work closely with the various team in architecting, designing and building ingestion pipelines to collect, clean, merge, and harmonize data from different source systems;
• Involved in architecting and scaling data analytics infrastructure on cloud environment; development of systems, architectures, and platforms that can scale large volume and variety;
• Architect and build ingestion pipelines to collect, clean, merge, and harmonize data from different source systems;
• Improve and optimize the workloads, processes to ensure that performance levels can support continuous accurate, reliable, and timely delivery of data products; ensure maximum database uptime;
• Monitoring of databases and ETL systems for database capacity planning and maintenance, monitoring, and performance tuning; diagnose issues and deploy measures to prevent recurrence;
• Construct, test, and update useful and reusable data models based on business data needs;
• Engagement and collaboration with product managers, software engineers, data analysts and data scientists to build scalable and data-driven platforms and tools;
• Collaborate with data stewards to establish and enforce data governance policies, best practices and procedures;
• Assist to maintain master data catalogue to document data assets, metadata and lineage;
• Implement and enforce data security best practices, including access control, encryption, and data masking, to safeguard sensitive data;
• Involved in managing production services that provide analytics capabilities to our various data users across the division.

About Bytedance

Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of more than a dozen products, including TikTok, as well as platforms specific to the China market, including Toutiao, Douyin, and Xigua, ByteDance has made it easier and more fun for people to connect with, consume, and create content.

Why Join Us

Creation is the core of ByteDance's purpose. Our products are built to help imaginations thrive. This is doubly true of the teams that make our innovations possible. Together, we inspire creativity and enrich life - a mission we aim towards achieving every day. To us, every challenge, no matter how ambiguous, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always. At ByteDance, we create together and grow together. That's how we drive impact - for ourselves, our company, and the users we serve. Join us.

About the Team

Nuverse is a gaming business unit in ByteDance. The Game Technology team is playing a significant role in the whole life cycle of the game. We are responsible for the development, testing, operation, SRE, and quality assurance of the user and operating system, and give strong support for game developing and publishing. Providing comprehensive and systematical solutions, support the good operation and commercialization of the game. Responsible for the design and implementation of the deployment architecture of the game's overseas game business, and ensuring the good operation of online services.

Job Description:

1. Participate in the construction and operation and maintenance of offline and real-time data warehouses for game business;

2. Participate in the optimization of the data ETL process and solve ETL-related technical problems;

3. Participate in data governance work under complex data link dependencies and multi-data content ecology;

4. Relying on ByteDance's big data solutions, quickly implement data solutions in the business.

Qualifications

Minimum Qualifications：

1. Bachelor's degree or above in computer-related majors, with more than 4 years of big data-related work experience;

2. Master most of the big data-related technologies such as Hive, Yarn, Spark, Flink, Kafka, HBase, understand their principles and be able to complete performance tuning;

3. Proficient in using HQL, and master at least one of Python, Java, Scala, and GO;

4. Familiar with the Linux operating system and proficient in Shell programming;

5. Be proactive at work and be able to independently analyze and solve problems;

6. Be responsible, have good communication skills and teamwork ability;

Preferred Qualifications:

1. Experience in the gaming industry or managing platform-type internet products will be an advantage.

ByteDance is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At ByteDance, our mission is to inspire creativity and enrich life. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.

Description

• Design, develop, and maintain scalable data pipelines using Spark and Scala to process large datasets.
• Implement and manage Elasticsearch clusters for efficient data retrieval and analysis.
• Collaborate with data scientists and analysts to understand data requirements and provide support for analytical solutions.
• Utilize Quantexa for entity resolution and network analytics to enhance data quality and insights.
• Monitor and optimize data workflows for performance, reliability, and scalability.
• Document data processes and ensure best practices in data engineering are followed.
• Participate in code reviews and contribute to the continuous improvement of our data engineering practices.

Requirements

• Proven experience as a Data Engineer, with a strong focus on Spark and Scala.
• Proficiency in Elasticsearch for search and analytics applications.
• Familiarity with Quantexa or similar tools for data enrichment and entity resolution.
• Experience with cloud platforms (AWS, Azure, GCP) is a plus.
• Strong SQL skills and experience with relational databases.

Responsibilities:

· Engage with clients to understand their business objectives, challenges, and requirements related to AI and Data solutions.

· Conduct discovery sessions to gather relevant information and identify opportunities where AI, LLM and Data Platforms can add value.

· Utilize knowledge of Data & AI capabilities to create compelling demonstrations tailored to client needs. Showcase how AI/LLMs can address specific use cases and deliver tangible business outcomes.

· Lead the execution of Proof of Concepts to validate the feasibility and effectiveness of solutions in addressing client requirements. Define success criteria, design POC workflows, and oversee the implementation process.

· Provide expert guidance and consultation to clients on technical aspects of Data Platforms, AI platforms, LLM technologies, fine-tuning methodologies, and model quantization techniques. Address client queries, offer insights, and recommend best practices of AI and Data Platforms

· Work closely with sales teams to support the development of winning proposals and presentations.

· Stay updated on industry trends, emerging technologies, and advancements in AI and Data domains. Share knowledge internally through training sessions, workshops, and documentation to empower sales teams and enhance organizational expertise.

· Cultivate strong relationships with clients, fostering trust and confidence in the capabilities of Data and AI platforms. Act as a trusted advisor, understanding their evolving needs and aligning solutions accordingly.

• Min 3 years of experience.
• At least 5 years of data-related working experience, with at least 3 years of hands-on experience in data management and data analytics in the finance, investment, banking, and asset management industries.
• Good understanding of the principles, key controls and processes relating to data management.
• Good at working with details and is meticulous in operations and tasks.
• Good understanding of data modelling.
• Good understanding on OLTP, Data Lake, Lakehouse technologies that may include knowledge of Snowflake, S3, AWS Glue, DeltaLake, DataBricks.
• Good understanding of CI/CD pipelines, DevOps, DataOps, and their applicability in financial services.
• Experience in working with databases using database technologies (e.g. MS SQL, Snowflake, Redshift and PostgreSQL) and data integration products (e.g. Informatica, Data Factory, Bash).
• Extensive data-related experience in programming languages eg Python, SQL, Scala, Javascript, and similar.
• Experience in working with business intelligence and data visualization tools e.g. Tableau, PowerBI.
• Experience with SDLC methodology and/or agile methodologies like Scrum and Kanban and its related applications eg Confluence and JIRA.
• Good team player, with strong analytical skills and enjoys complex problem solving.
• Experience in data engineering platforms and virtualization eg Denodo, Jupyter, O365.
• Excellent written and spoken English and strong presentation skillsets.
• Strong inter-personal and people leadership skills to interact with diverse stakeholders.

Responsibilities:

• Working closely with data analysts and business end-users to implement and support data platforms using best-of-breed technology and methodology.
• Implement and design robust and scalable solutions to meet business needs and take operational considerations into account. Demonstrate technical expertise in the assigned areas.
• Manage operations and maintain SLAs. Implement automation in data management. Collaborate with data engineering, architecture, and governance.
• Perform data and metadata quality, modeling, lineage, cleansing, onboarding, registration, discoverability, access controls, migration, optimization, and cataloging. Execute, maintain and manage the whole data lifecycle.
• Conduct requirement workshops with stakeholders, analyze and translate business and other requirements holistically into data strategies, plans, and actions.
• Cover all aspects of data distribution and data service.
• Design and implement scalable data pipelines and data service modules with robustness in mind to support the growing demands from business users.
• Analyze and resolve day-to-day operational incidents and advisory to business users.
• Listen to upstream changes, perform impact analysis and mitigate-modify-implement.
• Do impact analysis, inform and distribute to downstream users and applications.
• Analyze systems operations data (SLAs, customer satisfaction, delivery quality, team efficiency etc.) to identify actionable trends for continual improvements.
• Data, application, and system checking and testing (eg UAT), CICD and go-live.