Top Data Jobs in Singapore

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.

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.

Provide hands-on network implementation, configuration, installation and break/fix troubleshooting. Own portions of installations, escalate complex issues, document SOPs, maintain project administration, present to clients, and work toward professional networking certifications.

Provide advanced technical support and systems integration for networking solutions. Engage with clients onsite and remotely, produce technical specifications, reports and proposals, and assist in complex designs. Mentor junior engineers, coordinate implementation activities, troubleshoot networking issues, and maintain project documentation and SOPs.

Design end-to-end user journeys, information architecture, and interaction patterns for enterprise applications. Evaluate and refine AI-generated prototypes, ensure alignment with design systems and accessibility, facilitate usability assessments and stakeholder reviews, and collaborate with business analysts, product owners, and engineers to deliver consistent, user-centred solutions.

Provide expert-level technical support and systems integration for networking solutions. Engage clients, create technical specifications, assist in complex design, lead installations, troubleshoot networks, write reports and SOPs, and coach junior engineers.

Build and maintain end-to-end web applications: develop responsive React frontends, design backend services and RESTful APIs (Java/Node/Python/AWS Lambda), work with databases, troubleshoot performance issues, write tests, and collaborate with product, design, and engineering teams.

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.

Drive growth for Stripe Data Products by leading strategic sales, upsell, and expansion opportunities. Build executive-level relationships, develop account plans, manage complex negotiations, exceed revenue targets, and serve as a product and industry expert. Collaborate with sales, marketing, product, and operations teams; communicate customer feedback to inform the product roadmap; and support customer success and revenue growth.

Develops and operationalizes enterprise data management standards, governance frameworks, controls, tooling, playbooks, and learning materials. Partners with business units to implement data ownership, quality, metadata, lineage, risk management, and regulatory practices. Tracks governance outcomes, risks, dependencies, audits, and remediation. Serves as a data champion and coordinates regulatory and industry initiatives involving data and AI governance while promoting data accountability and literacy.

Support and optimize real-time financial market data systems, including exchange and client feeds. Integrate, normalize, monitor, and distribute low-latency market data while troubleshooting connectivity, data integrity, and infrastructure issues. Develop automation, tune system performance, conduct capacity planning, maintain documentation, and ensure compliance with exchange and regulatory requirements. The role also supports deployments and production incidents during weekends and public holidays.

Lead global finance digital transformation by aligning finance strategy with SAP capabilities, standardizing finance templates and architectures, managing cross-border demand, advising executive finance stakeholders, and driving change across international teams. The role requires delivering large-scale SAP Finance programs, designing consolidation solutions using SAP BPC or S/4HANA Group Reporting, integrating analytics and tax compliance, and improving close timelines, reconciliation efficiency, template adoption, and portfolio delivery.

Build and operate governed, audit-ready data foundations for client analytics and AI solutions. Responsibilities include designing ingestion pipelines, lakehouse and warehouse architectures, transformation and semantic layers, data quality, master data, lineage, privacy, residency controls, and AI-ready datasets. The role partners with AI engineers, data scientists, and client stakeholders, contributes reusable engineering accelerators, owns engagement-scale data architecture, and mentors junior resources. It is a hybrid Singapore-based Manager-level position with occasional APAC travel.

Serve as a trusted advisor for complex consulting engagements in Data Management. Lead solution scoping, architecture, feasibility assessment, design assurance, and implementation alignment with SimCorp standards. Own global consulting practice artifacts, improve methodologies, document best practices, enable consultants, and mentor aspiring architects. Collaborate with Sales, Product Management, Value Streams, project teams, and senior clients to resolve domain challenges and influence strategic architecture decisions.

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.

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.

Lead causal modeling and optimization for promotional spend across mobility, delivery, and logistics. Own end-to-end uplift and incrementality modelling, experiment and quasi-experiment design, heterogeneous treatment effect estimation, and budget-constrained allocation. Mentor data scientists, productionize models at scale, partner with product and engineering, and translate model outputs into business budget decisions.

Perform document retrieval, data entry, control checks, and processing of customer communications and PIN requests. Monitor exceptions, liaise with internal teams and vendors, support reporting and audits, validate scanned records, and participate in UAT and ad-hoc process improvements while ensuring compliance with SOPs and SLAs.

Design, build and operate enterprise-scale data and analytics platforms on GCP. Lead architecture, reliability and incident response for BigQuery/Dataproc/Spark workloads, implement IaC and CI/CD, drive SRE/observability, optimize performance and cost, mentor engineers and enforce security and operational best practices.

The Senior Data Scientist leads the design and development of machine learning models in healthcare, collaborating with cross-functional teams to deliver impactful insights and compliance.

As an Analyst in Data Science, you'll develop AI/ML solutions, collaborate across teams, and enhance customer experience through innovation. Responsibilities include coding, prototyping, and optimizing algorithms for business challenges.

Plan and execute end-to-end data transformation and migration for large, complex datasets. Lead extraction, validation, reconciliation, mock runs, trial loads, and final cutover while ensuring traceability, audit compliance, and database performance in high-scrutiny government-linked environments.

Analyze large-scale on-chain data to detect anomalous transactions, develop detection mechanisms and risk monitoring frameworks, apply supervised and unsupervised ML, identify malicious accounts via community-discovery algorithms, and design integrated on-chain/off-chain prevention and control systems.

Lead analytics for quick commerce growth across markets: design causal impact and ROI measurement, build BigQuery/dbt SQL models, produce dashboards and agentic AI solutions, influence senior stakeholders, and mentor junior analysts.

Lead application of data science, machine learning and generative AI to drive SME customer lifecycle outcomes. Translate business problems into models, build and deploy scalable production ML/AI solutions, partner with stakeholders and data engineering, monitor model performance, and promote responsible AI and MLOps best practices.