Top Data Jobs in Singapore

Gather and analyze business and risk requirements for Market Risk systems; create functional specifications, assess impacts, design test plans, conduct UAT and other testing, manage enhancement timelines, and provide BAU support for risk data sourcing, extraction, and analysis.

Design and deliver Qlik Sense dashboards, reports, data models, and AWS-based data pipelines. Translate stakeholder requirements into BI solutions, implement governance and security controls, optimize performance, manage Qlik environments, support UAT and adoption, troubleshoot data connectivity, and mentor team members on business intelligence and cloud data engineering practices.

Drive revenue growth by selling complex power and cooling solutions to data centre customers in Singapore and Johor Bahru. Manage the full sales cycle from technical discovery and solution development through presentations, quotations, contract negotiations, and order closure. Build strategic customer relationships, develop key accounts, monitor market and competitor activity, maintain CRM records, and collaborate with internal teams while meeting safety and operational standards.

Partner with global teams to drive international expansion through experiments, data pipelines, dashboards, metrics, and actionable insights. Translate business goals into analytical frameworks, collaborate with product and engineering teams, and deliver reporting, recommendations, and self-service tools that improve stakeholder data literacy and support growth decisions.

Audits and validates labeling annotation data for accuracy, consistency, guideline adherence, and regulatory compliance. Identifies errors and root causes, monitors quality KPIs, leads governance cycles, translates data trends into process improvements, and leads the NC Program. Collaborates with agencies and internal stakeholders across labeling operations.

Design and build scalable data infrastructure, backend services, data discovery and lineage systems, and fault-tolerant pipelines processing petabytes of data. Lead system design, code reviews, and technical contributions while developing cloud-based ETL solutions. Collaborate with machine learning and autonomy teams to improve data access, processing, and platform adoption.

Manage end-to-end data hall fit-out and ELV system design and delivery for data centers, from client consultation through handover. Coordinate consultants, contractors, system integrators, procurement, construction, testing, and commissioning. Lead designs for structured cabling, security, AV, automation, and related infrastructure while ensuring compliance with standards and client requirements. Provide technical support, resolve site issues, engage international clients, and help develop regional ELV and fit-out standards.

Design, implement, and manage large-scale Big Data infrastructure, including Hadoop, Spark, data lakes, storage systems, clusters, and Kubernetes environments. Optimize performance, scheduling, scalability, security, governance, and availability. Support data engineers and scientists, manage capacity planning and infrastructure deployments, and lead engineering teams. The role also involves building streaming and batch pipelines, supporting search workloads, and deploying AI/ML infrastructure.

Early-career research role implementing and running experiments on LLM reasoning, post-training alignment, and agentic AI for crypto markets. Tasks include literature synthesis, model implementation (PyTorch/Hugging Face), experiment tracking (Weights & Biases), and collaborating with engineers to translate research into production.

Design and build scalable onchain data infrastructure, including multi-chain ingestion, real-time and batch processing, data governance, search, storage, and APIs. Develop high-availability systems supporting blockchain explorers, wallets, DEXs, risk controls, token scoring, and related products. Drive technical decisions, cross-functional initiatives, reliability improvements, and AI-enabled engineering capabilities.

DBS is recruiting penultimate-year undergraduates for its 2027 internship program across Business, AI and Data Science, and Technology tracks. Interns must commit to a full-time 12- or 24-week placement beginning in May. Candidates should be self-motivated, adaptable, creative, resilient, and strong communicators. Applicants must submit a current CV and provide the correct internship code during the application process.

Lead SEAA's regional Data & Intelligence strategy, prioritize and deliver data, analytics and AI initiatives, guide platform and architecture choices, embed governance and responsible AI, drive data literacy and adoption, and build a high-performing data team aligned with global standards.

Leads technology and data governance for Prudential Financial Advisers Singapore. Responsibilities include implementing governance frameworks, coordinating audits and regulatory requests, tracking technology and data remediation issues, managing data owners and stewards, maintaining metadata and data lineage, designing data quality rules, overseeing governance checkpoints, and preparing management reporting. The role requires extensive stakeholder coordination across technology, risk, compliance, audit, and business teams in a regulated financial services environment.

Support financial planning, modeling, forecasting, and investment evaluation. Conduct market and competitor analyses, prepare reports and presentations for leadership, support due diligence, KPI and dashboard development, and drive automation to improve reporting and financial processes.

Build and maintain scalable ETL pipelines integrating structured and unstructured data. Automate data workflows, ensure efficient data movement, collaborate with analysts, scientists, and stakeholders, translate business needs into technical solutions, and maintain documentation and data governance compliance for secure, accessible data.

Analyze financial data and payment flows, assess data quality and reconciliation accuracy, build production tooling and dashboards, automate compliance reporting, analyze costs, and collaborate with engineering, product, and finance stakeholders. Present findings, participate in technical reviews, and communicate project progress while learning unfamiliar systems and solving operational problems.

Leads APAC data center development opportunities from site identification through land acquisition and execution readiness. Oversees technical and commercial due diligence, feasibility, utility strategy, permitting, risk management, governance, and investment approvals. Leads the APAC Investment Council, develops business cases, presents recommendations to executives, and provides portfolio oversight across budgets, schedules, risks, and capital deployment. Coordinates internal teams, consultants, landowners, utilities, regulators, and other stakeholders across regional markets.

Design and build scalable AWS data lakehouse platforms, including ETL/ELT pipelines, Apache Iceberg or S3 Tables implementations, data quality frameworks, governance, CI/CD, infrastructure as code, and production deployments. Optimize performance, cost, reliability, and scalability while documenting solutions and communicating architecture to technical and non-technical stakeholders.

Supports data collection, validation, cleansing, transformation, dashboard maintenance, exploratory analysis, reporting, documentation, and process improvement. Collaborates with operations, marketing, and revenue management stakeholders on analytics requests while developing skills in Power BI, Python, SQL, and hospitality analytics.

Lead data discovery, governance, and master data management for supply chain. Define processes, KPIs, and quality metrics; translate business needs into data requirements; resolve data issues; run workshops and collaborate across technical and business teams to improve data quality and implement solutions.

Own data product management across event tracking, data modeling, metric definition, dashboards, data governance, and BI solutions. Partner with business teams to understand needs, design end-to-end data solutions, standardize metrics, improve data quality, and drive adoption of data tools. The role requires strong cross-functional leadership, data ecosystem expertise, analytical problem-solving, and English and Mandarin Chinese proficiency.

Design, build, and maintain data models, ETL pipelines, dashboards, and APIs to support industry models, research, and consulting. Ensure data accuracy, completeness, and observability while integrating new datasets and cloud infrastructure. Collaborate with analysts and stakeholders to deliver robust, modular production data systems with minimal supervision.

Supports APAC subscriber analytics for Disney+, using SQL, Python, Excel, Tableau, and data warehouses to produce reports, clean and analyze data, visualize insights, improve dashboards and pipelines, and inform marketing, acquisition, retention, strategy, finance, and commerce decisions.

Lead high-impact data science initiatives from problem definition through production deployment and iteration. Design and deploy machine learning, AI, and analytical solutions, translate ambiguous business problems into measurable objectives, and partner with senior stakeholders on strategy and roadmaps. The role also provides technical leadership and mentorship across the data science community. Strong Python, SQL, statistics, machine learning, production modeling, and large-scale data experience are required.

Analyze billions of user behavior, fund-flow, and market records using PySpark, Hive, Trino, and SQL. Build feature pipelines, investigate data anomalies, and develop and evaluate machine learning models for risk detection. Translate model performance into business metrics such as detection rate, false-positive rate, and latency while owning a project stream end to end.