Top Data Jobs in Singapore

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.

Lead cloud managed-services sales by identifying, developing, negotiating, and closing complex outsourcing opportunities. Serve as a trusted executive advisor, align AWS, Azure, and Google Cloud solutions with client needs, manage pipelines and sales strategies, drive renewals, upselling, cross-selling, revenue, and margin growth, and collaborate with presales, delivery, and client teams to ensure satisfaction and reduce churn.

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.

Supports Senior Project Managers in delivering E&M-driven data centre construction projects. Responsibilities include project documentation, meeting materials, progress reporting, stakeholder communication, site-visit support, activity and deliverable tracking, and risk escalation. The role coordinates project information across clients, consultants, contractors, and internal teams throughout project phases.

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.

Leads business data readiness for a data migration project, including requirements gathering, data cleansing coordination, quality issue tracking, stakeholder and customer communications, cutover planning, validation, hypercare, and audit-ready documentation. The role translates technical findings into business actions, coordinates UAT and readiness activities, supports transition and go-live stabilization, and manages risks, dependencies, approvals, and issue resolution across business and technical teams.

Develop and deploy AI/ML and generative-AI solutions: collaborate with stakeholders, research methods, perform data wrangling and feature engineering, maintain deployed models/assistants, build backend APIs and frontend interfaces, document products and fix security issues.

Design, build, and maintain large-scale batch and real-time data pipelines, ETL/ELT processes, and data stores (data lakes, marts, warehouses). Perform data extraction/cleaning (including web scraping), integrate data silos, develop backend APIs, and collaborate with cross-functional teams in an Agile CI/CD environment.

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.

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.

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.

Own end-to-end robotics data collection: translate research needs into collection protocols, run multi-site collection operations, maintain rigs and pipelines, define KPIs, diagnose data quality, and align researchers, engineers, and operators to deliver training-ready datasets.

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.

Lead technical consulting teams for pre-sales, delivery, maintenance and offshore vendor management for customer communication and enterprise content management solutions. Own technical solutioning for bids, ensure project delivery and support SLAs, manage vendor operations, coach staff, track operational metrics, and drive continuous improvement across professional services.

Serve as ASOs single front door for Operations demands across Asia, translating business needs into prioritized initiatives, managing demand pipeline, shaping improvement using AI/data/APIs, and coordinating stakeholders to deliver operational efficiency, compliance, and value realization.

Lead development and deployment of deep learning and probabilistic models for multi-physics engineering problems. Architect scalable data pipelines, collaborate with simulation engineers, drive R&D, mentor junior team members, and work directly with customers to integrate models into production, including onsite customer collaboration and presentations.

Manage and mentor a team of data scientists/analysts to build data-driven solutions: oversee data collection, cleaning, modeling, ML development, SQL reporting, microservices/API deployments, visualization, and lifecycle management from pilot to production.

Lead rollout of APAC data culture and literacy strategies, design and deliver engagement and training initiatives, produce executive communications and presentations, coordinate cross-functional multi-country deliverables, and support stakeholder management to drive data-driven decision-making.

Lead strategic APAC accounts to drive retention and growth: execute account plans, collaborate with sales and operations, monitor KPIs, support renewals/pricing, resolve client issues, and improve account management processes.