Top Data Jobs in Singapore

Supports corporate compliance across international data center operations by developing and maintaining policies, screening high-risk vendors and customers, conducting risk assessments, monitoring regulatory changes, delivering compliance training, and investigating breaches and whistleblower reports. The role also manages corrective actions, audit trails, compliance dashboards, and implementation of data privacy and governance requirements across multiple jurisdictions.

Lead cost management for MEP data centre construction projects from initiation to completion. Oversee cost planning, estimating, reporting, value engineering, risk and contract management, client/stakeholder engagement, team leadership, invoicing via Dynamics 365, and business development activities to meet budgetary and quality targets.

Manage client relationships as a subject matter expert, collaborating with Account Executives to drive revenue, engage clients, and provide product insights for innovative solutions.

Design, build, and maintain scalable data pipelines, data lakes, and databases; ingest and map customer financial datasets; monitor pipeline reliability; translate business requirements into data flows and analytical insights to ensure high-quality, usable data.

Leads advanced analytics, measurement, reporting automation, and AI-enabled analytics solutions for clients and internal stakeholders. Develops marketing mix models, attribution, predictive models, segmentation, dashboards, data pipelines, and analytics-ready datasets using SQL, Python, cloud platforms, and BI tools. Presents insights to stakeholders, supports client consulting and business development, mentors analysts, and advances data quality, governance, measurement methodologies, and analytical capabilities.

Lead Customer 360 data engineering initiatives across Customer and Sales domains. Design data integration, ingestion, curation, governance, quality, harmonization, and common data models. Build scalable cloud-based data capabilities and integration pipelines while supporting data products, use cases, and analytics. Collaborate with business owners, regional partners, and technology teams to define strategy, roadmaps, prototypes, and MVPs, serving as a subject matter expert in Customer 360 data.

Design, build, deploy, and improve OCR, computer vision, and LLM-based systems for intelligent document understanding. Develop production ML services in Python, monitor quality and performance, run controlled experiments, optimize model behavior, and collaborate with product and engineering teams to deliver AI capabilities.

Lead design and delivery of AI-powered automation, Copilot agents, advanced analytics, and monitoring solutions for global Healthcare Compliance. Translate business problems into scalable data-driven solutions, partner with governance and technology teams, and mentor stakeholders while implementing APIs, BI dashboards, process mining, and Cloud-based generative AI capabilities.

Lead single-threaded product and technical ownership for Client Intelligence & Data, defining APIs and event-driven architectures to deliver merchant-facing analytics, KPIs, and reports. Drive platform strategy toward AI-driven insights, enforce production reliability and automated QA, champion You Build It You Run It culture, partner cross-functionally to scale multi-tenant analytics capabilities, and prioritize work using evidence-based frameworks.

Perform high-level video captioning, action-based timeline segmentation, and visually-verifiable action labeling. Review and correct AI-generated captions, meet accuracy benchmarks, follow strict guidelines, and complete certification.

Leads the bank’s AI and data assurance strategy, overseeing model validation, AI risk mitigation, data quality, privacy, governance, controls, monitoring, regulatory reporting, stakeholder training, and team leadership. Ensures AI and data initiatives are ethical, compliant, secure, reliable, and aligned with financial-services regulations and internal policies.

Lead development and execution of company-wide data, analytics, and AI strategy. Build and manage multidisciplinary teams, govern data quality and compliance, oversee architecture and production ML/AI deployments, select and maintain data platforms and tooling, partner with business stakeholders to deliver high-impact use cases, and measure ROI while driving innovation and adoption.

Design, deploy, and maintain AWS and Databricks data infrastructure, data lakes, and scalable ETL pipelines. Build custom ingestion services and connectors using Airbyte, Go, and Python; optimize performance, reliability, monitoring, and data quality. Implement cloud data governance, security, access controls, encryption, and compliance practices while collaborating with platform engineers, analysts, and stakeholders.

Design and govern enterprise network solutions for large Singapore accounts. Lead presales activities (proposals, RFPs, POCs), produce technical specifications, guide sales, and transition solutions to delivery while providing hands-on technical leadership.

Develop and deploy analytics and predictive models to improve logistics operations. Lead cross-functional initiatives, providing insights and fostering data-driven decision-making.

Designs and develops scalable enterprise data services and Big Data applications using Spark, Kafka, Spring Boot, Java, Python, Kubernetes, Iceberg, and S3. Responsibilities include data ingestion and transformation, microservices and REST APIs, Spark optimization, CI/CD, production support, cloud-native architecture, and Generative AI integration. The role also establishes engineering standards and collaborates with cross-functional, cross-regional teams in an Agile environment.

Supports distribution and logistics analytics by maintaining material master data, assisting with month-end accruals, cleansing freight-spend data, and enhancing Excel reports with Python. Builds dashboards comparing volume, budgets, forecasts, and actuals, publishes reports in Power BI, investigates outliers, coordinates with internal and external providers, and updates user documentation.

Drive new-business growth for Parameta Solutions’ OTC market data and financial intelligence offerings. Responsibilities include prospecting, qualifying leads, managing the sales pipeline, conducting needs assessments, presenting tailored solutions, collaborating with SDRs, maintaining Salesforce records, and achieving sales targets. The role requires consultative B2B selling experience in data, analytics, or financial technology, strong communication skills, and the ability to operate effectively in a fast-paced environment.

Lead behavioral science adoption across the bank, diagnose customer and business behavioral barriers, design behaviorally informed interventions, and oversee statistical and quasi-experimental analysis. The role partners with executive stakeholders, develops experiment narratives, manages cross-business-unit testing, drives customer experience impact, and delivers behavioral science training.

Design, build, secure, and operate highly available data centre networks, including leaf-spine fabrics, routing, switching, firewalls, load balancers, segmentation, and inter-data-centre connectivity. Troubleshoot mission-critical network issues, improve reliability, and manage capacity and performance. Develop Network-as-Code automation for provisioning, validation, testing, compliance, and drift detection. Apply telemetry, AI, and AIOps techniques while collaborating with cloud, compute, storage, cybersecurity, and application teams.

Design and operate enterprise AI platforms for a banking group, including multi-agent frameworks, LLM inference infrastructure, MLOps pipelines, and hybrid AWS/on-premises deployments. Build production AI services, optimize GPU utilization and inference latency, manage model lifecycles, establish CI/CD and observability, and provide daily platform operations. The role requires strong Python, cloud, AI framework, inference-stack, Kubernetes, infrastructure-as-code, and DevOps expertise, with AVP and VP experience levels ranging from 4+ to 8+ years.

Design, build, and operate scalable logging and operational data platforms across on-premise, government cloud, AWS, Azure, and hybrid environments. Responsibilities include log ingestion, routing, enrichment, storage, indexing, search, streaming, data integration, Infrastructure as Code, CI/CD, security, governance, reliability engineering, monitoring, incident response, and operational support. The role also defines schemas, data contracts, retention policies, platform interfaces, and reusable capabilities for downstream engineering, analytics, dashboards, and automation consumers.

Designs and operates observability across on-premises, cloud, hybrid infrastructure, applications, and networks. The role establishes OpenTelemetry instrumentation standards, telemetry collection, dashboards, SLIs, SLOs, alerting, and operational health indicators. Responsibilities include integrating telemetry sources, supporting incident investigation, improving service reliability, managing retention and security requirements, automating deployments with Infrastructure as Code, and maintaining runbooks. The engineer collaborates with application, infrastructure, network, security, platform, and operations teams and participates in on-call support.

Build and operate production-grade data pipelines across on-premises and cloud environments. Responsibilities include data ingestion, ETL/ELT, transformation, modelling, quality validation, lineage, monitoring, secure integration, and reusable analytical data products. The role supports dashboards, reporting, machine learning, and operational analytics while implementing CI/CD, Infrastructure as Code, data governance, reliability controls, incident response, and production support.

Own pricing and retail analytics initiatives, including decision systems, reports, metrics, statistical analysis, and business insights. Lead end-to-end projects, translate complex data for stakeholders, influence product and strategy decisions, and collaborate with Pricing, Retail Commerce, 3P Commerce, Promotions, developers, and analysts. Ensure data quality, improve reporting systems, solve ambiguous problems, and provide strategic guidance in a fast-paced e-commerce environment.