Top Data Jobs in Singapore

Supports enterprise data governance initiatives across data lineage, data quality, data catalogues, taxonomy, discovery, and impact analysis. Assists with data analysis, reporting, dashboard development, stakeholder requirements, process improvements, and ad hoc risk-management projects. The internship provides exposure to BCBS239 principles, regulatory reporting, data governance frameworks, and tools for managing enterprise data assets.

Designs and delivers data architecture solutions, creates secure production code, evaluates technologies, guides architecture governance, and applies AI-assisted practices to improve data frameworks, resiliency, and security.

Design and deploy real-time ML models and credit risk frameworks to detect fraud and assess merchant lending risk. Translate business needs into scalable analytics, monitoring, and decision-support tools. Partner with product, engineering, and operations to productionize models and improve risk visibility and decision quality.

Summer internship applying data science, AI, software engineering, analytics, and automation to manufacturing and business problems. Interns analyze datasets, build dashboards/reports, develop automation or software solutions, and present findings to improve operational efficiency and support digital transformation.

Serve as ASOs single front door for Operations demands across Asia, translating business needs into prioritized initiatives, managing demand pipeline, shaping improvement using AI/data/APIs, and coordinating stakeholders to deliver operational efficiency, compliance, and value realization.

Lead data acquisition and partnership activities for Transport AI, developing a prioritized multimodal data roadmap, negotiating data access with agencies and industry, enforcing data standards and governance, building secure ingestion platforms, and working with legal, cyber and AI teams to onboard datasets for analytics and AI use cases.

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 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.