Top Data Jobs in Singapore

Designs, engineers, secures, and operates enterprise-scale data, analytics, AI, and agentic platforms on GCP. Leads cloud architecture, infrastructure automation, IAM and governance, Kubernetes operations, CI/CD, DevSecOps, production troubleshooting, and reliability improvements. Acts as an escalation point for complex issues, establishes engineering standards, leads design reviews, mentors engineers, and evaluates emerging cloud and AI technologies.

Drive enterprise and commercial B2B sales for Salesforce Agentforce and Data 360. Identify, qualify, and develop opportunities; conduct technical discovery; present scalable AI and data solutions; create compelling points of view; and align Salesforce capabilities with customer objectives. Collaborate with account teams and cross-functional partners throughout the sales cycle while translating complex AI, cloud data, and platform concepts into measurable business value and exceeding sales targets.

Owns regional MCC data infrastructure, dashboards, reporting standards, data governance, and client database quality across SEAO markets. Translates client and marketing data into actionable insights for engagement, retention, loyalty, planning, and investment decisions. Coordinates with headquarters and market teams, supports tool enhancements and testing, ensures privacy compliance, trains data users, and builds a collaborative data-driven community.

Leads architecture, security, operations, cost management, and governance for an enterprise GenAI and data platform on Google Cloud. Designs LLM agents, RAG solutions, secure tool-enabled workflows, private networking, IAM, observability, and capacity models. Oversees distributed data pipelines, cloud migration, performance optimization, risk approvals, and engineering standards while mentoring teams and engaging security, vendors, and business stakeholders.

Lead architecture, reliability, scalability, modernization, and operational excellence for enterprise data and visualization platforms. Responsibilities include building Big Data infrastructure, managing Trino, Superset, Tableau, and related tools, migrating legacy applications to cloud-native environments, improving CI/CD, implementing observability with ELK, Prometheus, and Grafana, optimizing capacity and costs, overseeing production support, and mentoring SRE and DevOps teams in a regulated banking environment.

Build and scale a financial data platform for investment teams. Responsibilities include evaluating structured and unstructured datasets, developing reliable ETL workflows, improving data infrastructure, and creating reusable tools for data analysis and quality checks. The role works closely with portfolio managers and quantitative researchers and takes projects from requirements through delivery.

Design, build, optimize, and maintain scalable data pipelines for mission-critical national security analytics systems. Responsibilities include processing large datasets, ensuring data quality and governance, implementing testing and monitoring, troubleshooting complex pipeline issues, and experimenting with agentic AI systems and LLM workflows. The role also involves collaborating with product and engineering stakeholders to deliver reliable data products.

Leads research data and analytics operations, including funding and publication reporting, data governance, quality control, process improvement, dashboards, automation, and intranet management. Coordinates stakeholders across university offices, establishes data standards and workflows, produces management insights, oversees research data management, and guides team members in delivering accurate, timely work.

Leads design and development of scalable cloud-based data and analysis platforms. Responsibilities include architecture, implementation, testing, deployment, troubleshooting, documentation, unit testing, and Agile/Scrum collaboration. The role requires full-stack development expertise, strong Java skills, frontend framework experience, distributed databases, REST services, and cross-functional communication. Kubernetes, cloud infrastructure, and CI/CD experience are preferred.

Conduct statistical analysis, quantitative research, and data modelling to support university decision-making, institutional planning, rankings, and outcome improvement. Build databases, improve data collection and validation processes, analyze complex datasets, and communicate insights to diverse stakeholders across the university.

Leads Vantage’s renewable energy and clean technology strategy across APAC. The role originates, structures, negotiates, and delivers energy transactions and campus solutions involving renewables, BESS, microgrids, hydrogen, fuel cells, and on-site generation. Responsibilities include securing power capacity, managing utility and government relationships, developing strategic partnerships, guiding investment decisions, and overseeing projects from origination through commercial operation. The Director collaborates across business, construction, operations, finance, sustainability, and executive teams to support data center growth and decarbonization.

Designs, builds, and operates secure AWS-native data pipelines and platforms for batch and event-driven workloads. Develops Airflow workflows using Python and SQL, implements tested data transformations, and integrates enterprise, security, and operational data sources. The role embeds data quality, lineage, observability, governance, encryption, access controls, and monitoring. It also contributes to CI/CD, infrastructure as code, documentation, code reviews, incident analysis, and cross-functional solutions supporting risk and regulatory needs.

Develop quantitative models and data pipelines for MetaBrain decision-intelligence software. Responsibilities include preparing reliable datasets, building forecasting, segmentation, ranking, scoring, or optimization models, validating uncertainty and business value, and operationalizing reproducible analytical workflows with data tests, monitoring, scenario outputs, and explainability.

Prospect and secure new B2B clients for financial data and analytics products across APAC. The role involves qualifying leads, conducting needs assessments, delivering tailored presentations, managing CRM records and pipeline health, collaborating with SDRs, and consistently meeting sales targets. Candidates should have B2B sales experience in data, analytics, or financial technology, strong consultative communication skills, Salesforce experience, and business-level English. Mandarin, Cantonese, or Korean is advantageous.

Develop cloud-native data and AI products, assess emerging AI technologies, build microservices, and implement production-ready algorithms. Responsibilities include collaborating with product, engineering, and industry teams throughout the product lifecycle; deploying AI applications; and ensuring transparency, fairness, scalability, security, and cost effectiveness. The role requires expertise in machine learning, prompt engineering, AI agents, RAG, geometric algorithms, and 3D modeling technologies.

Develop decision-intelligence models and reusable analytical services for market research and advisory use cases. Responsibilities include preparing and validating data, building forecasting, segmentation, scoring, and optimization models, running simulations, quantifying uncertainty, documenting assumptions, and packaging analyses into reproducible notebooks, pipelines, or services. The role also requires monitoring model and data changes, explaining results to advisors, and supporting governed AI-enabled business solutions.

Analyze customer and payment-message screening performance across DBS operating countries. Develop and backtest recommendations for detection rules, matching logic, thresholds, and risk scoring; evaluate risk coverage, false positives, data quality, and operational efficiency. Translate findings into requirements and test scenarios, support UAT and implementation validation, provide regulatory and audit evidence, and advise Compliance, Technology, Operations, and business stakeholders as a screening analytics subject matter expert.

Manage MEP cost management across major construction and data centre projects, including cost plans, estimates, budgets, tendering, procurement support, commercial negotiations, change control, payment applications, forecasts, final accounts, and contract administration. The role provides commercial advice, manages cost risks, supports stakeholder relationships, and contributes to multidisciplinary project delivery and continuous improvement.

Leads cost management and commercial advisory services for mission-critical data centre projects. Responsibilities include cost planning, estimating, procurement strategy, tender evaluation, contract support, post-contract cost control, forecasting, change management, risk assessment, client advisory, stakeholder engagement, and team mentoring. The role requires substantial MEP or CSA expertise, preferably in data centre environments, and experience across pre-contract and post-contract project phases.

Supports cost management for data centre and mission-critical construction projects across pre- and post-contract phases. Responsibilities include preparing estimates, budgets, cost plans and reports; supporting feasibility, value engineering, procurement and tender evaluations; reviewing quotations, payments, variations and final accounts; monitoring project costs; maintaining commercial records; and collaborating with clients, consultants, contractors and project teams. Experience in CSA or MEP packages is encouraged.

Own and grow assigned client accounts by driving new business, expansion, renewals, client satisfaction, and revenue growth. Manage opportunities, pipelines, forecasts, partners, vendors, and internal resources while serving as the primary client contact. Identify client needs, connect them to NTT DATA solutions, develop demand, and support governance, risk, and compliance initiatives.

Lead the design, development, and delivery of AI and GenAI solutions across business domains. Act as an AI Product Owner, translating business challenges into scalable solutions, managing cross-functional delivery squads, and measuring adoption and business value. Develop machine learning, LLM, RAG, agentic AI, orchestration, and governance capabilities while mentoring technical teams and advancing reusable AI standards and assets.

Develop and support batch and streaming data pipelines, data models, ingestion workflows, orchestration, cloud infrastructure, and backend services for banking data platforms. The role also supports AI knowledge bases, vector database pipelines, embeddings, document processing, RAG workflows, and semantic search. Responsibilities include monitoring data quality, troubleshooting pipeline issues, participating in testing and code reviews, and collaborating with engineering, AI, and business teams.

Designs and develops secure, scalable client solutions across cloud and on-premises environments. Responsibilities include gathering requirements, evaluating architectures, creating technical specifications and roadmaps, developing proofs of concept, integrating infrastructure and applications, supporting technical changes, consulting with clients, and contributing to go-to-market services.

Build and maintain production machine learning models and AI products for player personalization, recommendation, propensity scoring, and Next Best Action systems. Collaborate with engineers, analysts, and product stakeholders to translate business needs into pragmatic solutions, integrate models into production, and expand AI-driven player engagement capabilities. Contribute to AI agent architectures, automation workflows, and the roadmap for new ML product opportunities.