Top Data Jobs in Singapore

Design, build, and maintain full-stack applications and data pipelines to enable data discovery and sensemaking. Integrate modern technologies, debug and optimize systems, participate in code/design reviews, and communicate solutions to stakeholders.

Lead design, build, test and deploy scalable data-intensive web analytics systems and APIs for national-security use cases. Guide performance, reliability, proofs-of-concept (including agentic AI), mentor juniors, and collaborate with product and stakeholders to deliver impactful solutions.

Manage and optimize a scalable, secure Data Exploration Platform: deploy, patch, tune performance, enforce access controls, support stakeholders with technical guidance, and drive platform improvements and best practices for data analytics and visualizations.

Lead development and maintenance of the banks Data and AI risk management framework, set data risk appetite and controls, translate regulatory expectations, codify standards, and ensure consistent definition and reporting of data risks and control gaps across the Group.

Lead development and refinement of the banks AI risk framework; apply frameworks to use cases; review higher-risk AI applications; liaise with business, technology, and control owners; track remediation and emerging risk themes; prepare governance materials and monitor regulatory developments.

Lead and execute the regional data, analytics, and AI strategy while overseeing implementation, collaboration, team development, and governance compliance.

Assist in data collection and annotation processes to enhance self-driving software development, collaborating with teams for data quality and sensor calibration.

The Senior Data Engineer will design and implement data pipelines, modernize systems, and ensure data governance on cloud platforms. Responsibilities include real-time data processing, ETL workflow creation, and collaboration with teams on data solutions.

Support APAC revenue growth and go-to-market initiatives by analysing merchant transaction data, scheme performance, and payment economics. Build pricing models, recommend routing optimizations, design enterprise pricing, and partner with sales to structure multi-regional commercial deals to protect margins and increase approvals.

The intern will support APAC growth initiatives, analyze data with Python/R and SQL, and design BI dashboards using Power BI, while assisting in program management tasks.

Own the end-to-end analytics lifecycle: define measurement frameworks, build and maintain data pipelines and dashboards, analyze product/behavioural/model data, support experiment/A-B test design, ensure data quality, and communicate insights to influence product and model decisions.

Architect and operate enterprise network security as L3/L4 escalation: design and manage firewalls, IDS/IPS, VPNs, NAC, cloud network security, Zero Trust/SASE, perform incident response and root-cause analysis, mentor junior teams, author HLD/LLD, automate tasks, and support DR and security policy development to meet SLAs.

Structured graduate programme offering hands-on exposure to cloud, data, AI/ML, application development, automation, infrastructure and cybersecurity through client projects, mentorship, training, and industry certifications to launch technology careers.

Provide advanced L3/L4 managed services and automation across Cloud, Security, Networking, Applications and Collaboration. Troubleshoot and resolve escalated incidents, perform root cause analysis, implement automation, coach L1/L2 teams, manage changes, support projects and disaster recovery, and document and share knowledge to meet SLAs.

Manage and grow assigned Financial Services Industry (FSI) accounts, drive new logo acquisition, meet revenue and margin targets, minimize churn, and expand services. Use Salesforce/CRM to manage pipelines, coordinate global stakeholders, develop account strategies, and translate client needs into actionable solutions throughout the buying lifecycle.

Sell cloud managed services to enterprise clients by developing relationships, generating demand, managing pipelines, structuring managed services deals, and coordinating internal delivery and vendors through to contract close.

Lead delivery and scaling of generative AI data programs across multiple projects: capacity planning, vendor management, quality consistency, process automation, financial control, risk mitigation, client reporting, and team enablement.

Lead and scale portfolios of generative AI data programs (collection, labeling, evaluation). Manage capacity planning, vendor SLAs, quality consistency, process automation, budgets, risk, stakeholder reporting, and coach PMs/coordinators while ensuring data security and compliance.

Act as the technical lead for strategic customers across pre-sales, architecture, implementation, retention/expansion, and product feedback. Build POCs, run technical workshops, ensure integrations scale, and translate customer needs into product features.

Design and govern core business metrics and analytics frameworks for claims data products; craft analytics narratives for dashboards; evaluate analytics/AI agent outputs; write production-quality analytics code and collaborate with engineering, product, and clinical teams.

Drive end-to-end product analytics for user growth and product strategy: define metrics, design and analyze A/B tests, handle PB-scale behavioral and transactional data, build dashboards, predictive models, and deliver actionable insights to product and business stakeholders.

Design, develop, and evaluate AI-driven solutions for sustainable living. Collect and preprocess multimodal datasets, build data pipelines and experiments, analyze model performance, iterate on models, and collaborate on publications, reports, and demonstrations.

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.

The role involves managing data ingestion pipelines, collaborating with scientists for data optimization, and ensuring efficient data collection to support AI model training.

Manage and deliver HSE oversight for data centre construction projects: conduct site audits and safety walks, report incidents and near-misses, ensure inductions and contractor compliance, prepare monthly safety assessments, and drive corrective actions to achieve zero incidents.