Top Data Jobs in Singapore

Lead technical delivery of projects, design kdb+ architectures for time-series data, mentor developers, and drive innovation in kdb+ systems.

Responsible for sales results in mid-size and large accounts, developing customer relations, analyzing sales data, and driving innovative products.

Own the marketing data ecosystem for TOKEN2049 and SuperAI: build automated dashboards, analyze multi-channel campaign performance, manage audience segmentation and CRM hygiene, audit tracking (GTM/GA4), run A/B tests, and optimize conversion funnels to maximize ticket sales, sponsorships, and brand awareness.

Lead development and deployment of GenAI, RAG, ML and Agentic AI solutions for continuous audit, risk assessment, testing and reporting. Collaborate with auditors, data engineers and cross-functional teams to design, evaluate, and scale production-grade models and MLOps on cloud infrastructure. Introduce innovative analytics to improve audit effectiveness and coach stakeholders.

Perform full-stack on-chain and product analytics: query on-chain data, profile ecosystem actors, benchmark protocols, define KPIs, build dashboards, and translate findings into actionable briefs for strategy, BD, product, and growth teams.

Design, validate, and deploy AI algorithms for digital health projects. Lead technical innovation, support data platform development and retrospective analysis, collaborate with clinicians and biostatisticians, publish findings, prepare technical reports, and mentor junior AI researchers.

Provide L3 managed services for cross-technology client infrastructure: resolve complex incidents, ensure SLA compliance, mentor junior staff, create knowledge articles, collaborate with vendors, drive automation and operational improvements across cloud, security, networking and application domains.

Provide L3 managed services support across cloud, security, networking and applications. Proactively resolve high-complexity incidents, ensure SLAs, mentor L2 staff, create knowledge articles, engage vendors, and input into automation and operational improvements.

Design, build, and maintain analytics-ready data marts using dimensional modeling; partner with analytics and business teams to deliver documented datasets; implement resilient batch and real-time data pipelines; architect cloud data infrastructure; enforce data standards, validation, and monitoring to ensure data integrity and scalability.

Design, build, and optimize offline and real-time data pipelines and warehouses for product data. Lead end-to-end R&D for online product data pipelines, ensure timeliness and accuracy, perform Flink-based real-time processing and performance tuning, and enable business growth through data products and services.

Build and maintain the risk-control data warehouse, develop thematic metrics and indicators, design offline and real-time data architectures, optimize data pipelines, and deliver reporting and API interfaces for the data mart to support risk control business lines.

Evaluate data centre investment opportunities, build and maintain financial models, prepare investment memos and presentations, perform market research and due diligence, coordinate external advisors, and provide ad-hoc portfolio and performance analysis to support senior management.

Take end-to-end ownership of backend features and SaaS services in a microservices architecture. Design, implement, deploy, and operate scalable, reliable Node.js services. Work with Redis Streams, MongoDB, Kubernetes, and ensure test coverage, performance tuning, and collaboration with cross-functional teams.

Lead company-wide performance intelligence: build central dashboards and KPI frameworks, produce executive reports, run deep metric analyses (P&L, funnels, retention), create forecasts and ROI models, and design self-serve data infrastructure and automation to guide strategic decisions and resource allocation.

Design, prototype, and deploy personalization, recommendation, and search models using large-scale behavioral and transactional data. Build end-to-end ML pipelines, run A/B tests and offline/online evaluations, integrate LLM/LLVM-based models, collaborate with product and engineering teams, and monitor/iterate models to improve discovery and user engagement.

Implement and configure Collibra data catalog and lineage (technical and business), integrate metadata from ETL, data lake/DWH and core banking systems, map end-to-end lineage, enforce MAS-aligned data governance, validate metadata quality, and manage stakeholder delivery and reporting.

The Software Engineer for Data Infrastructure & Acquisition at Speechify will enhance data collection, manage infrastructures, and work with AI scientists to develop large-scale datasets.

Design, build, and operate backend services and data pipelines to ingest, process, enrich, and deliver large scientific, media, and geospatial datasets. Implement REST APIs, event-driven and streaming systems, and Kubernetes-based production infrastructure to support machine learning and agentic AI applications. Collaborate with scientists and ML engineers to translate requirements into scalable, reliable solutions.

Lead end-to-end cost management for large-scale data centre and mission-critical projects. Define cost strategies, manage cost planning, estimating, forecasting, contract administration and commercial risk. Act as client lead, mentor cost teams, drive value engineering, controls and governance, and support business development in the data centre sector.

Support and optimize large-scale Spark/YARN jobs and storage (S3/EMR). Build job-profiling, cost-analysis, AI-assisted automation, monitoring/alerting (Prometheus, Flink/Spark), and internal ops tooling to improve stability and reduce costs.

Lead electrical design and engineering for data centre projects in Sydney. Oversee project delivery, manage budgets and clients, mentor junior engineers, and integrate industry innovations for energy-efficient, high-performance facilities. Support multidisciplinary teams and foster client relationships.

Lead mechanical design and engineering for data centre projects, manage multidisciplinary teams and budgets, engage clients, mentor junior engineers, and integrate innovative, energy-efficient solutions.

The HSE Manager is responsible for ensuring health and safety compliance in data centre construction and operations, leading safety initiatives, and monitoring performance metrics.

Build and maintain regional data pipelines and architecture, automate ETL and reporting, transform data for analytics, and collaborate with business stakeholders to identify data gaps and implement solutions. Share best practices and support dashboard/report automation.

Lead global data engineering for wealth management: define roadmap, design scalable pipelines, oversee data lakes/warehouses, select technologies, optimize performance, enforce data governance, and manage a distributed engineering team to deliver high-quality financial data solutions.