Top Data Jobs in Singapore

Lead the data-quality stream to deliver CDE metadata, governance and audit‑ready artefacts for BCBS239 compliance. Manage a multidisciplinary team, engage senior stakeholders, run governance and change initiatives, and build Power BI monitoring dashboards. Translate data governance and lineage concepts into implementable controls and ensure global adoption across business and functional areas.

Leads the enterprise strategy, roadmap, operating model, and delivery of data products and Data-as-a-Service capabilities. Oversees data product engineering, governance, security, adoption, monetisation, and value measurement across the bank. Establishes a Data Products Centre of Excellence, builds cross-functional teams, enables self-service data consumption, and partners with senior stakeholders, technology, risk, compliance, and governance teams to deliver scalable, controlled, and commercially valuable data capabilities.

Supports electrical engineering design delivery for data center and mission-critical projects across APAC. Responsibilities include defining project objectives, schedules, resources, and deliverables; applying engineering judgment; managing technical risks and quality standards; mentoring team members; supporting client relationships; and contributing to bids, proposals, thought leadership, and regional service delivery.

Leads data-driven industrial optimization projects from requirements gathering through deployment and monitoring. Responsibilities include building scalable data pipelines, integrating industrial data from IoT devices, sensors, test benches, and SCADA systems, performing data quality checks and exploratory analysis, developing machine learning models, creating Power BI and Flask dashboards, supporting digital twin simulations, and developing RAG-based chatbot solutions.

Early-career data scientist role to analyze user and content data, build metrics, design recommendation strategies (recall, ranking, cold-start, diversity), run A/B tests, evaluate experiments, explore LLM/multimodal applications, and improve data pipelines and feature logging.

Lead design and development of scalable data infrastructure and self-service tooling for data engineering teams. Provide technical leadership, implement robust systems (Kubernetes/Terraform/GitOps), ensure quality through testing and maintenance, troubleshoot production issues, and collaborate cross-functionally to deliver reliable data platforms.

Lead design and build of high-performance distributed data infrastructure and AI enablement platforms. Optimize systems internals and JVM performance, implement lakehouse and real-time streaming, develop scalable vector indexing and AI knowledge platform, own SDLC for petabyte-scale systems across global regions, drive engineering best practices, and mentor mid-level engineers.

Partner with Product and Engineering to analyze large datasets, run experiments, build statistical models, define product metrics, forecast outcomes, and deliver insights that drive product strategy and roadmap decisions.

Lead design, build, and operate distributed, large-scale (batch/streaming) data platforms and pipelines. Drive technical decisions, performance optimization, data architecture (lakehouse), tooling standards, third-party integration, and mentor junior engineers to enable company-wide data-driven capabilities.

Lead a Singapore-based team to design, build, and maintain scalable data infrastructure and self-service developer tooling. Implement robust, maintainable systems, ensure quality through testing and troubleshooting, collaborate cross-functionally, and mentor engineers while staying current with emerging technologies.

Develop and deploy predictive models and AI/agentic AI solutions using large-scale manufacturing data. Perform EDA, data extraction/cleansing, feature engineering, and statistical modeling. Collaborate with data engineers, manufacturing engineers, UX, and stakeholders to translate insights into operational improvements that boost yield, quality, efficiency, and business value.

Design and lead end-to-end enterprise data and GenAI architectures, drive cloud migration/modernization, define GenAI/Copilot/agentic patterns (RAG, embeddings, vector search), establish MLOps/LLMOps and governance, ensure Responsible AI and security, and act as trusted technical advisor across presales through production.

Manage employment screening, reference checks, screening-vendor governance, work pass administration, RNF licensing, employee declarations, regulatory reporting, and HR compliance processes. Maintain records, procedures, dashboards, and metrics while ensuring data privacy and regulatory compliance. Partner with Compliance, Talent Resourcing, vendors, and other stakeholders to resolve issues, support audits, monitor service levels, and improve HR processes and employee experience.

Collects, validates, analyzes, and visualizes APAC digital and e-commerce data to produce dashboards, reports, and actionable business insights. Partners with marketing, product, e-commerce, distribution, and agency teams to measure KPIs, support digital growth strategies, manage brand health reporting, and improve reporting processes. Presents findings to stakeholders and senior management while managing agency deliverables.

Evaluate and annotate 3D meshes, GLB files, images, and short videos for model training and error resolution. Identify whether assets are artist-created or AI-generated, and detect geometry defects, topology errors, and scene inconsistencies. Requires hands-on 3D modeling experience, familiarity with Blender or Maya, strong mesh-topology knowledge, English proficiency, and a suitable computer with dedicated graphics capabilities.

Analyze operational, financial, maintenance, and resident feedback data to identify trends and service gaps. Develop and maintain dashboards and KPIs, automate reporting, improve data governance, and provide actionable insights to operations and management. Prepare presentations and support ad-hoc studies to inform strategic planning and enhance resident experience.

Design and maintain data pipelines, build data warehouse models, optimize dbt Cloud workflows, improve CI/CD and DevOps practices, and support AI initiatives involving Data Genie. Collaborate with business stakeholders to resolve data issues, deliver actionable insights, and support operational needs across business units.

Leads mechanical engineering design delivery for hyperscale and co-location data center projects. Oversees technical quality, project objectives, schedules, resources, budgets, and multidisciplinary coordination. Builds client partnerships, supports bids and proposals, contributes to thought leadership, and drives sector growth. Requires extensive data center or mission-critical engineering experience, commercial acumen, professional engineering qualifications, Uptime Institute ATD certification, and eligibility for Baseline or higher AGSVA clearance.

Drive new enterprise business development and own the full sales cycle, from prospecting and discovery through negotiation and contract closure. Build qualified pipeline, manage Salesforce forecasts, develop account and opportunity strategies, engage C-suite stakeholders, position enterprise technology solutions, lead consultative negotiations, and coordinate internal teams and partners to deliver compelling proposals and profitable growth.

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.

Leads analysis, mining, modeling, and visualization of large-scale transactional, operational, and customer data. Partners with compliance teams to prioritize analytical use cases, support regulatory requirements, improve business efficiency, and translate complex findings into actionable recommendations. Oversees multidisciplinary analysts, manages stakeholder data requests, assesses business changes, and develops analytical systems using machine learning, big data technologies, and visualization tools.

Leads VAST Data’s APJ pre-sales function, personally supporting complex AI infrastructure opportunities and executive customer engagements. Builds, coaches, and retains a distributed regional solutions engineering team; sets technical strategy; partners with sales, channels, alliances, product, and engineering; influences roadmap through customer and competitive insights; and represents VAST with partners, analysts, press, and the NVIDIA ecosystem. Requires extensive APAC travel and a Singapore base.

Analyzes sales channels, business performance, revenue, and acquisition trends; develops dashboards and reports; designs and calculates sales incentive programs; monitors targets; and presents actionable insights to stakeholders. The role collaborates with Sales, HR, and other business teams, supports strategic decision-making, and applies banking and wealth management industry knowledge to identify optimization and innovation opportunities.

Develop multilingual LLMs for Bahasa Indonesia and regional languages. Responsibilities include creating datasets for pretraining, fine-tuning, alignment, and evaluation; training and scaling models; implementing safety and guardrail systems; researching efficient methods; and collaborating with product and engineering teams to deploy reliable, production-grade AI solutions.

Own data and AI product initiatives end to end, from defining problems and data requirements through coding, evaluation, launch, monitoring, improvement, and adoption. Build production systems with AI coding agents, create release evaluation suites, track product and operational metrics, measure business impact, collaborate with technical and business teams, and document products through runbooks, design notes, evaluation reports, and training materials.