Top Data Jobs in Singapore

Lead semiconductor manufacturing analytics: own test analytics strategy, build analytics platforms, implement quality screening (PAT, SBL, outlier detection), integrate foundry/OSAT/MES systems, design data infrastructure and automation (ETL, dashboards), and drive operational excellence across wafer, assembly, test, and quality.

Provide on-the-ground administrative, logistical and personal/family support to the Executive Director in Singapore; coordinate with the Hong Kong EA; arrange and process business travel and expenses; support other senior executives' travel/expense needs; liaise with internal teams, vendors, schools and service providers; handle confidential matters and urgent requests with discretion.

Own commercial analytics and analytics engineering: translate business questions into structured analysis, build trusted dbt datasets and semantic metrics, create decision-ready dashboards, improve data quality, and partner with Commercial, Pay/Risk, Marketing, and Finance to drive business outcomes.

Provides online facilitation and subject-matter guidance to international data science students. Responsibilities include Python and data science tutoring, one-on-one and group sessions, academic and research support, reference guidance, assessment marking with detailed feedback, discussion forum management, and prompt personalized responses to student questions. The role is remote and requires daily availability during specified IST hours.

Provides online facilitation and subject-matter guidance for master's-level big data management students. Responsibilities include tutoring, supporting academic writing and research, recommending resources, marking assessments, managing discussion forums, and responding promptly to student needs. The role requires expertise in big data modeling, distributed storage and computing, large-scale analytics, Hadoop, Apache Spark, SQL, and algorithms such as PageRank. The facilitator works remotely with diverse international students and is available daily from 2:30 to 7:00 PM IST.

Ensure reliability, availability, and performance of data centre IT operations. Manage day-to-day monitoring, incident lifecycle, capacity planning, documentation, observability and network monitoring, remote management tools, and define SRE metrics (SLO/SLI/error budgets). Collaborate with facilities on power, cooling, and physical infrastructure.

Build, test, and deploy scalable, data-intensive web search and analytics systems for national-security use. Design architectures, write maintainable code and tests, monitor system health, optimise performance, deliver proofs-of-concept, and support mission-critical deployments.

Manage user acquisition and retention funnels; design, implement, track, and optimize multi-platform acquisition campaigns; own BI and CRM dashboards; measure marketing channel performance; run experiments to improve ROI; work in a small team and take ownership of growth projects.

Design, develop, and deploy large-scale data systems to support cybersecurity products for threat detection, investigation, and analysis. Build scalable, high-availability architectures, microservices, and RESTful APIs with CI/CD. Monitor system health and telemetry, scale systems for growing data volumes, and collaborate with cross-functional teams to meet operational needs.

Design, develop, test, and maintain scalable data processing applications and APIs. Build and operate data pipelines, improve system resiliency, participate in code reviews, document solutions, and prepare production-ready data for AI applications while collaborating within an Agile team.

Lead design, build and maintain scalable, low-latency large-scale data pipelines. Optimize performance, ensure data quality and governance, troubleshoot critical systems, mentor junior engineers, and collaborate with stakeholders to deliver mission-critical data products.

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 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.

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.

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.

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.