Top Data Jobs in Singapore

The role involves ensuring end-to-end performance and power readiness of Data Center SSD programs through technical execution, analysis, and leadership across teams.

Coordinate product-line efforts and portfolio metrics to drive operational improvements. Develop change initiatives and timelines, maintain FITS inventory, troubleshoot entitlement issues, handle client tickets per SLA, perform month-end activities, manage market-data system testing/validations (DACS, EMRS), liaise with vendors, and maintain controls and documentation.

Manage and optimize high-load Microsoft SQL Server databases, including advanced T-SQL development, query and execution-plan optimization, indexing, locking, memory, disk performance, AlwaysOn availability, maintenance, recovery, security, integrity checks, monitoring, and incident resolution. Support analysts and ML engineers with reliable data access across databases reaching tens of terabytes.

Build and maintain scalable enterprise data platforms, pipelines, integrations, and reusable data products for global manufacturing operations. Implement data governance, quality monitoring, metadata, lineage, and master data practices. Develop cloud-native, batch, streaming, and event-driven solutions supporting analytics, AI, reporting, smart factories, and digital twins. Collaborate with architects, engineers, data scientists, and operations stakeholders while applying DevOps, observability, and CI/CD practices.

Analyze e-commerce data across Reolink’s official website and Amazon platforms to generate insights, improve profitability and performance, and support product decisions. Build data pipelines, dashboards, APIs, and e-commerce metrics systems; validate data quality, investigate issues, and collaborate with product management, engineering, design, and data engineering teams to drive data-informed growth.

Coordinates local and overseas Community Immersion Programme projects from planning through follow-up. Manages timelines, stakeholders, logistics, mentor and partner matching, participation tracking, reporting, dashboards, and feedback analysis. Uses data, digital tools, automation, and AI applications to improve programme processes and efficiency while supporting programme growth and stakeholder engagement.

Analyzes international trade, tariff, customs, shipment, and trade agreement data; prepares reports and recommendations on risks, costs, duty optimization, and trade strategy. Monitors import/export compliance across China, Europe, and Asia, maintains SAP/MIC trade data, resolves discrepancies, supports customs reconciliation, researches regulatory changes, and identifies automation and process improvement opportunities. Collaborates with logistics, supply chain, finance, legal, compliance, and regional trade teams.

Lead end-to-end SAP data migration for large-scale S/4HANA implementations and global rollouts. Define migration strategy and governance, oversee data assessment, cleansing, extraction, transformation, validation, mock loads, cutover, and go-live support. Manage migration tools, data quality, reconciliation, stakeholder workshops, distributed teams, testing, risk tracking, and executive reporting across business functions and countries.

Maintain bond and issuer reference data across treasury systems, ensuring accurate attributes, timely request processing, and adherence to SLAs and controls. Investigate data issues, collaborate with dealers, finance, custodians, and processing teams, and support UAT, process documentation, STP improvements, and data transformation initiatives. The role requires financial markets knowledge, bond settlement experience, strong analytical skills, and proficiency with Murex, Bloomberg, custodian systems, and Microsoft 365.

Lead and coordinate card-network financial integrity programs (fraud, disputes, chargebacks). Maintain governance, trackers, remediation, controls, and documentation. Translate network requirements into internal policies and playbooks, coordinate cross-functional remediation, prepare leadership/audit materials, identify process gaps, and standardize global program execution across Compliance, Risk, Legal, Product, and Operations.

Build and operate production-grade AI data pipelines and financial knowledge services for equities content. Responsibilities include processing text, tables, documents, and multimedia; creating knowledge bases and search indexes; engineering RAG retrieval and citation systems; integrating LLMs and NLP models; managing orchestration, APIs, quality, cost, observability, reliability, and scalable production operations.

Lead infrastructure engineering for Market Data Services, architecting and modernizing cloud and on-prem systems. Drive complex programs, validate AI-assisted recommendations, ensure resiliency, security, and compliance, collaborate with stakeholders, provide 3rd-level production support, and adopt automation and monitoring to reduce recurring issues.

Lead the go-to-market and sales strategy for LMAX’s market data business across APAC. Identify, qualify, negotiate, and close opportunities with brokers, banks, hedge funds, and other financial-market clients. Develop pricing, licensing, and distribution models; serve as a market-data subject matter expert; and collaborate with account management, technology, product, and commercial teams to drive revenue, market share, product improvements, and successful client partnerships.

Build and operate ingestion and ELT pipelines, maintain metadata repositories and internal data tools, implement data-quality checks, reconcile financial data, investigate anomalies, and support analysts. The role includes backend service development, production ownership, AWS-based platform work, and integrating LLM/RAG capabilities into data tools.

Analyze and reconcile financial data, investigate discrepancies, trace data origins, and automate manual validation checks using SQL and Python. Build and maintain Finance dashboards, document datasets, and make missing or inconsistent data visible. The role involves production data, reporting pipelines, version control, review processes, and clear communication of findings. No professional experience is required, but candidates should be numerate, detail-oriented, comfortable questioning data, and able to explain technical discrepancies clearly.

Leads an L2 service recovery team supporting critical banking systems. Oversees major incident resolution, escalations, root cause analysis, service-level adherence, runbooks, post-incident reviews, and continuous improvement. Partners with engineering and infrastructure teams to implement permanent fixes, supports disaster recovery and business continuity activities, ensures regulatory compliance, and maintains 24/7 coverage while developing team capability.

Owns data and AI governance initiatives within a technology unit, including operating-model design, policy and controls adoption, data quality management, assessment reviews, responsible data use, AI governance, risk monitoring, issue remediation, audit readiness, and stakeholder escalation. The role advises data domain leaders, coordinates with enterprise risk and data functions, and strengthens data governance culture across a complex, regulated banking environment.

Designs complex, cross-domain technology solutions spanning applications, infrastructure, cloud, and on-premises environments. Collaborates with clients and internal teams to assess requirements, evaluate architectures, create technical plans, develop roadmaps, deliver proof-of-concept implementations, and resolve problems. Applies enterprise architecture methodologies and standards while mentoring colleagues and supporting consulting engagements.

Designs, builds, deploys, and operates scalable cloud data lakehouse platforms and production ETL/ELT pipelines. Responsibilities include data architecture, open table formats, automated data quality, governance, access controls, CI/CD, infrastructure as code, analytics and AI enablement, documentation, monitoring, incident response, and cost optimization. The role collaborates with technical and business stakeholders across Databricks, Spark, AWS, and Microsoft Fabric environments.

Build and maintain scalable batch and real-time data pipelines for information security and digital risk analytics. Translate business and risk requirements into technical specifications, data models, ETL solutions, and production-ready data products. Support testing, deployment, monitoring, documentation, and production issue resolution while applying data governance, access control, auditability, and secure-by-design practices. Collaborate with business, risk, technology, and platform stakeholders in a regulated banking environment.

Internship data analyst supporting dashboard monitoring, user behavior and content ecosystem analysis, A/B test evaluation, campaign performance analysis, data quality assurance, and metric documentation. The role uses SQL and Excel to derive insights on engagement, retention, conversion, and creator ecosystems, while collaborating with product and operations teams in a blockchain and digital assets environment.

Supports marketing analytics for OCBC Consumer Banking by exploring data, developing predictive models, managing campaign reporting, defining customer metrics, executing targeted campaigns, and supporting segmentation and product initiatives. Partners with business stakeholders, data engineers, and data scientists to develop analytics solutions, recommendation engines, data pipelines, and automated campaign execution that improve customer acquisition, cross-selling, activation, and marketing effectiveness.

Leads global data architecture, governance, master data management, analytics, and business intelligence strategy. Owns data models and roadmaps, ensures data quality and regulatory compliance, prioritizes BI initiatives, and delivers reporting solutions. Identifies automation and process improvement opportunities while supporting digital transformation. Collaborates with stakeholders, application teams, and enterprise architects to translate business needs into scalable solutions and contribute to enterprise architecture planning.

Lead technical strategy for payments optimization to balance conversion, fraud risk, and cost. Design and implement advanced optimization algorithms, guide experimentation and causal inference, collaborate with product and engineering to deploy ML systems at scale, influence product strategy, and mentor junior data scientists.

Lead architecture of a governed, reusable data, knowledge, and skills platform on Databricks to power analytics, AI agents, and real-time decisioning. Design data, semantic, and skills layers, enforce Governance-as-Code, enable regional data residency, and build agent interfaces and APIs while partnering with Data Science, Product, and Risk teams.