Top Data Jobs in Singapore

Partners with manufacturing, planning, and supply chain stakeholders to solve complex operational problems. Designs and deploys digital twins using operations research, mathematical optimization, and discrete event simulation. Develops production-grade applications, data pipelines, models, APIs, and user interfaces. Converts large datasets into decision-support tools, drives solution deployment across global manufacturing sites, and collaborates with data scientists, AI engineers, product owners, and domain experts.

Operate and maintain critical database systems supporting manufacturing and engineering. Responsibilities include database installation, upgrades, patching, access management, backups, monitoring, performance tuning, incident resolution, disaster recovery, capacity planning, reporting, automation, and business continuity. The role provides on-call support, collaborates with customers on database requirements, improves operational reliability, and evaluates emerging database technologies and AI-assisted tools.

Designs and owns scalable batch and streaming data pipelines, data models, and infrastructure for business and AI use cases. Partners with engineering and cross-functional teams to deliver reliable solutions, monitoring, governance, and data quality improvements. The role involves distributed data systems, real-time analytics, knowledge retrieval, and AI-ready infrastructure, with work based five days per week in Singapore.

Own regional data center vendor strategy and end-to-end colocation deals, including planning, RFPs, commercial negotiations, execution, vendor relationship management, QBRs, budgeting, spend review, and invoice approval. The role coordinates with legal, operations, capacity planning, network strategy, and security teams across multiple geographies to expand and optimize Cloudflare’s data center footprint.

Lead modelling and analysis roadmap for FX products: forecast and monitor FX volatility, optimise trade execution with statistical/ML models, run customer and profitability analyses, and partner with product, trading, risk, and engineering to translate insights into trading and product decisions.

Leads engineering strategy, organization, performance, quality, and talent development for the CIS Domain in Singapore. Manages discipline heads across design, product ownership, software, cloud platforms, and innovation. Oversees engineering staffing, delivery, continuous improvement, Agile and Lean practices, digital development environments, and collaboration across multidisciplinary teams. Partners with domain leadership on business development and ensures engineering capabilities support cloud, software, AI, cybersecurity, and user-centric products and services.

Provides second-line oversight and credible challenge for AI, privacy, and data risks across APAC. Leads monitoring and testing reviews, control assessments, regulatory engagements, issue remediation, governance reviews, and executive reporting. Translates regulatory expectations into controls, testing methods, evidence requirements, and practical guidance while partnering with business, technology, legal, data, cybersecurity, and model risk stakeholders.

Develops and deploys advanced analytics and machine learning solutions across operational datasets. Responsibilities include data extraction, cleaning, feature engineering, exploratory analysis, model development, dashboard creation, production monitoring, retraining, documentation, and system integration. The role requires translating analytical findings into actionable insights for engineering and operations partners while working across the full data science lifecycle.

Leads technical AI risk management for the bank’s AI ecosystem, including GenAI, foundation models, RAG architectures, AI platforms, and agentic systems. Defines technical control expectations, risk indicators, monitoring, access, security, resilience, and data protection requirements. Provides independent challenge to technology and engineering teams, evaluates emerging AI risks and regulations, and supports the evolution of AI governance frameworks and regulatory engagement.

Analyzes complex supply chain data to diagnose performance drivers, evaluate planning scenarios, quantify trade-offs, and deliver evidence-based recommendations. The role uses Python, SQL, statistical methods, scenario modeling, and sensitivity analysis while collaborating with planners, data scientists, and automation teams. It translates ambiguous business problems into structured analytical frameworks and validates model outputs against operational constraints. The position focuses on decision support and analytical problem-solving rather than production machine-learning engineering, data pipelines, or application development.

Analyze inkjet product event and printer telemetry data to generate customer usage insights, enable predictive analytics, and create Power BI dashboards monitoring trends and customer experience behavior. The internship requires full-time availability for 5–6 months and strong data analysis, creative thinking, and proficiency with office productivity tools.

Supports supply chain data collection, cleaning, organization, analysis, reporting, statistical analysis, and visualization. The intern identifies trends, collaborates with team members, contributes to data-driven process improvements, and develops practical analytics experience. The role requires a 5–6 month full-time commitment beginning in May 2027.

Support and operate enterprise market data platforms and vendor feeds across AWS and on-premises environments. Responsibilities include monitoring, incident troubleshooting, production upgrades, migrations, failover testing, application onboarding, vendor coordination, entitlement reviews, audit support, documentation, and automation improvements. The role requires market data platform expertise, real-time data distribution knowledge, scripting, high-availability production support, and ITSM familiarity.

Drive enterprise sales of FactSet’s data and off-platform technology solutions to buy-side, sell-side, and strategic partner clients. Identify opportunities, manage sales pipelines, develop value propositions, collaborate with sales, implementation, consulting, and product teams, and serve as a subject-matter expert on financial data workflows. Build client relationships, deliver training, provide product feedback, and develop strategies that support client satisfaction, retention, and revenue growth.

Designs and delivers enterprise Data, Generative AI, and Agentic AI solutions for customers. Responsibilities include architecting modern data platforms, AI agents, RAG and orchestration workflows; implementing secure, scalable production systems; applying DevOps, MLOps, observability, and Responsible AI practices; leading technical workshops and customer co-development; mentoring engineers; and creating reusable architectures, accelerators, and engineering patterns.

Leads the global marketing function’s strategy, integrated planning, brand management, campaigns, partnerships, digital and content initiatives. Makes investment and prioritization decisions across markets, manages agencies, coaches marketing teams, and partners with Communications and PR. The role requires translating company strategy and go-to-market priorities into international marketing plans while managing budgets, senior stakeholders, and cross-functional execution in a fast-growing, matrixed organization.

Lead corporate communications across global markets, including corporate narrative, media relations, crisis and issues management, executive communications, reputation management, and multi-market coordination. The role develops messaging, oversees media engagement and agencies, advises executives and country teams, and ensures consistent communications standards. At Director level, it also includes team leadership, operating-model design, and strategic counsel to senior leadership.

Designs and maintains scalable automated testing frameworks for web applications, APIs, databases, and end-to-end processes. Develops test strategies, plans, cases, and quality standards; integrates automated tests into CI/CD pipelines; manages defects and quality metrics; and supports Agile delivery. The role collaborates with technical and business stakeholders, drives continuous improvement, and mentors junior QA professionals.

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.

Manage health, safety, and environmental compliance for data center construction projects. Responsibilities include conducting site visits, safety walks, audits, inductions, incident investigations, safety observations, corrective-action follow-up, and HSE reporting. The role supports project management across multiple sites, coordinates with contractors and stakeholders, and promotes zero-incident performance.

Build and maintain scalable data engineering infrastructure for scientific, sensor, and operational data. Responsibilities include feature engineering pipelines, data quality monitoring, versioning, lineage, drift detection, data contracts, governance, sensor ingestion, synthetic data pipelines, and MLOps data layers. The role requires strong Python, SQL, pipeline design, and data lifecycle fundamentals, with integration into AWS-based AI platforms and progressive ownership of real-time systems.

Build the intelligence layer of a railway data platform by developing end-to-end machine learning solutions for time-series forecasting, anomaly detection, and operational decision intelligence. Responsibilities include data discovery, feature engineering, model deployment, monitoring, scalable data pipelines, automated maintenance alerts, and AI-agent reasoning. The role also involves translating model outputs into dashboard requirements, communicating uncertainty to stakeholders, and collaborating with designers, product managers, and railway engineers.

Leads end-to-end data centre construction projects, including planning, budgeting, scheduling, design coordination, construction oversight, contractor management, commissioning, handover, safety, and quality assurance. The role oversees critical infrastructure such as electrical distribution, backup power, cooling, fire protection, and BMS/DCIM systems while managing risks, changes, governance, and stakeholder communication.

Lead data centre project delivery from planning through completion, managing schedules, budgets, quality, safety, statutory compliance, procurement, consultants, contractors, stakeholders, reporting, and site coordination. Develop junior team members, oversee multidisciplinary teams, maintain master and short-term programmes, manage inspections, resolve issues, and ensure project milestones and objectives are achieved.

Build and maintain scalable data platforms, databases, ETL processes, and data pipelines across relational and NoSQL systems. Integrate data from multiple sources, optimize SQL queries and database performance, perform data quality checks, troubleshoot complex data issues, and support secure, compliant healthcare data processing. The role also includes testing, code reviews, architecture optimization, and collaboration with technical and non-technical stakeholders.