Top Data Jobs in Singapore

Lead design and delivery of site-level data architectures, pipelines and analytics to enable real-time decision-making and AI-enabled solutions across manufacturing, quality, engineering and supply chain in a regulated (GMP) environment. Drive digital roadmap execution, governance, adoption, and continuous improvement with cross-functional stakeholders.

Designs, develops, and deploys Power Platform applications, automated workflows, RPA desktop flows, Dataverse solutions, and Copilot Studio agents. Integrates solutions with Microsoft 365, Dynamics 365, SharePoint, Azure, and enterprise AI services. The role supports proof-of-concept engagements, ALM, governance, security, compliance, technical documentation, knowledge transfer, client delivery, and post-launch stabilization.

Lead MLOps efforts by designing, building, and maintaining ML pipelines, implementing CI/CD workflows, mentoring engineers, and ensuring data privacy and compliance.

Analyze large-scale transactional, operational, and customer datasets; build visualizations, machine learning models, and experiments; translate complex findings into clear recommendations for operational teams and executives; and apply analytical software, databases, visualization tools, and programming languages in a fast-paced blockchain environment.

Design, build, and scale data infrastructure for LLM training, fine-tuning, evaluation, and RAG. Implement and maintain data architectures, pipelines (batch and streaming), org-level IAM and governance, cost/performance optimizations, analytics/dashboarding, AI-assisted ops and internal automation tools, and support multi-cloud production workloads.

Leads architecture and development of large-scale batch and real-time data platforms and pipelines. Ensures data quality, governance, reliability, observability, scalability, and cost efficiency while building self-service capabilities. Supports analytics, machine learning, and generative AI teams with trusted data infrastructure. Establishes engineering standards, mentors engineers, and drives platform health across multiple teams. The role requires expertise in data integration, distributed processing, data modeling, cloud platforms, CI/CD, and infrastructure automation.

Perform high-risk document and account servicing tasks, act as SME, manage exceptions and escalations, support audits and regulatory requests, reconcile operational reports, liaise with vendors, ensure SOP compliance, and drive process improvements while providing backup team lead coverage.

Manage daily Data team operations, research and analyze datasets, build internal and external reports (including an annual Startup Ecosystem Ranking), and maintain/improve Python scripts and data infrastructure to deliver actionable insights.

Design, develop, and deploy production-ready AI applications and scalable DataOps/MLOps pipelines for avionics manufacturing. Build LLM/RAG/agent-based solutions, integrate enterprise and manufacturing systems, implement CI/CD and containerized deployments, ensure security/compliance, and collaborate with stakeholders to deliver measurable operational improvements.

NTT DATA's Associate Graduate programme provides structured learning, mentorship, and hands-on exposure across cloud, data, AI/ML, application development, automation, infrastructure and cybersecurity. Graduates work on real client projects, earn certifications, build technical and professional skills, and explore specialised career pathways such as Cloud Engineering, Data Engineering, AI/ML, and Cybersecurity.

Manage and grow strategic regional ASEAN accounts as a quota-carrying client manager. Drive ACV, revenue, renewals and expansions; build executive relationships; identify cross-sell/upsell opportunities; coordinate country teams, solution specialists and delivery stakeholders; manage full sales lifecycle, forecasting, pipeline, and regional account governance.

Develop, train, fine-tune, evaluate, and deploy AI/ML models and LLM-powered data products. Build end-to-end model pipelines, feature engineering, monitoring, and production deployment. Apply generative AI for summarization, classification, knowledge extraction and semantic search. Collaborate with product, engineering, and business teams and integrate third-party tools and open-source models.

Leads regional Payment Operations transformation, service excellence, and AI-enabled digital initiatives. Drives predictive analytics, automation, workflow digitization, and scalable technology solutions using Python, SQL, Power BI, Power Automate, APIs, and Generative AI. Oversees projects from business case through implementation, benefits realization, governance, operational readiness, and regional rollout. Partners across Operations, Technology, Product, Risk, Compliance, vendors, payment networks, and country teams to improve productivity, resilience, controls, quality, and client outcomes.

Leads commercial activities for global data center customer prospects, including strategic pricing, bid and RFP support, contract risk assessment, deal approvals, costing, renewals, churn analysis, sales forecasting, and pipeline analysis. Partners with Sales, Product, Legal, and other business units to improve profitability, digitize quotation processes, and implement commercial initiatives. Requires strong knowledge of ICT and data center markets.

Lead digital, data, and AI adoption by partnering with business leaders, designing enablement and change programs, supporting pilots, measuring adoption KPIs, and advising stakeholders to scale user-centric analytics and AI solutions.

Provide hands-on support for treasury financing activities: prepare drawdown/rollover notices, maintain financing documents and trackers, coordinate KYC and lender requests, manage compliance and lender reporting inputs, liaise with banks, lawyers, valuers, and internal teams, and support treasury automation and ad-hoc tasks.

The Staff Software Engineer will design high-performance backend services, manage distributed state, ensure system resilience, and implement cloud-native architectures with advanced engineering principles.

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 enterprise data product and Data-as-a-Service strategy, delivery, operationalization, governance, and adoption within a regulated banking environment. Build reusable, governed data products supporting analytics, AI, reporting, and business decision-making. Establish operating models, metadata and lineage standards, quality controls, self-service consumption channels, and Centre of Excellence practices. Partner with senior stakeholders, engineering, technology, governance, risk, and business teams to prioritize use cases, manage delivery, enable AI context, and track measurable value.

Lead design and delivery of DayOne's global insurance program, govern broker relationships, embed insurance into construction and commercial contracts, manage complex claims, report program performance to governance bodies, own insurance budgeting, and build a small insurance team supporting global data center growth.

Lead the development and deployment of AI models focusing on computer vision and text processing. Responsible for enhancing model performance and collaborating with teams to meet business needs.

Design, build, and maintain data models, ETL pipelines, dashboards, and APIs to support industry models, research, and consulting. Ensure data accuracy, completeness, and observability while integrating new datasets and cloud infrastructure. Collaborate with analysts and stakeholders to deliver robust, modular production data systems with minimal supervision.

The role involves analyzing datasets to optimize learning processes, developing strategies for faculty engagement, and conducting action research in educational settings.

Design, build, and maintain the Consumer Banking Singapore DataMart; extract, clean and analyze data; create dashboards and automated reports; support stakeholders with insights, decision support, and data-driven business cases; document data catalog and improve data processes.

Triage and resolve Master Data Management (Party, Risk, Reference) issues in Stibo STEP, run targeted data-cleansing sprints, monitor data quality dashboards, support releases/UAT, and maintain documentation and playbooks to prevent recurring data issues.