Senior Data Engineer, Data Platform, Singpass

The Government Technology Agency (GovTech) is the lead agency driving Singapore's Smart Nation initiatives and public sector digital transformation. As the Centre of Excellence for Infocomm Technology and Smart Systems (ICT & SS), GovTech develops the Singapore Government's capabilities in Data Science & Artificial Intelligence, Application Development, Smart City Technology, Digital Infrastructure, and Cybersecurity.

As a Senior Data Engineer in the Data Platform team, you will design, build, and operate highly reliable data systems that handle critical data at scale. You will work across data engineering, software engineering, distributed systems, and platform engineering to ensure that data can move securely and reliably across Singpass.

Responsibilities:

• Design, build, and operate scalable data platforms and distributed data systems that support both real-time and batch workloads.
• Build and evolve event-driven architectures and stream-processing systems, modelling complex event flows to support fraud detection, product insights, business intelligence, and real-time capabilities.
• Develop robust data ingestion and processing pipelines with strong guarantees around data quality, freshness, availability, and integrity.
• Design platform capabilities that make it easier and safer for engineering, data, and product teams to consume and work with data.
• Build observability and telemetry to monitor platform health, including data freshness, schema drift, pipeline performance, failures, and other DataOps signals.
• Diagnose complex production issues across applications, data pipelines, infrastructure, and distributed systems, and address their root causes.
• Design and evolve architectures that meet stringent requirements for security, reliability, resilience, scalability, and maintainability.
• Write secure, high-quality, production-ready code and contribute to strong engineering standards through design reviews and code reviews.
• Improve developer experience through better tooling, automation, platform abstractions, and engineering workflows.
• Manage technical debt and continuously improve the reliability, performance, and operability of the platform.
• Work closely with software engineers, data scientists, product managers, cybersecurity specialists, and other teams to translate product and operational needs into scalable technical solutions.

As a Senior Data Engineer, you will also be expected to:

• Provide technical leadership for complex data platform initiatives from design through production.
• Lead architecture and technical design discussions, helping teams navigate trade-offs across scalability, reliability, security, performance, and delivery.
• Establish and champion engineering and DataOps best practices across the platform.
• Identify opportunities to simplify architectures, strengthen platform capabilities, and improve engineering productivity.
• Mentor engineers and raise engineering standards through technical guidance, design reviews, code reviews, and knowledge sharing.
• Influence technical decisions beyond your immediate area and collaborate across teams on shared platform and architecture challenges.
• Support technical hiring and contribute to building engineering capability within Singpass.

We value strong engineering fundamentals and technical judgment over experience with any particular technology. We are looking for engineers who:

• Have strong software engineering fundamentals and experience building production-grade distributed or data-intensive systems.
• Have experience designing and operating event-driven architectures, messaging systems, and/or stream-processing systems.
• Understand data platform concepts such as ingestion, transformation, storage, data modelling, data quality, governance, observability, and data lifecycle management.
• Can reason about distributed-system challenges including scalability, fault tolerance, consistency, reliability, and performance.
• Understand how to design systems for both real-time and batch data-processing workloads.
• Build systems with strong operational practices, including monitoring, alerting, incident response, and observability.
• Think carefully about security, privacy, and data governance when designing systems that handle sensitive information.
• Have strong debugging and problem-solving skills and are comfortable investigating complex problems across multiple layers of a system.
• Are comfortable making and communicating technical trade-offs through architecture discussions, design documents, and code reviews.
• Take ownership of systems beyond implementation, including deployment, operations, reliability, and continuous improvement.
• Communicate effectively and collaborate across engineering, product, data, cybersecurity, and other stakeholder groups.
• Mentor other engineers and help raise the technical bar of the wider engineering team.

Experience with technologies or concepts such as Kafka or other event-streaming platforms, stream processing, cloud data infrastructure, data lakes or warehouses, schema management, DataOps, feature stores, and large-scale distributed systems would be valuable, although we do not expect candidates to have worked with every technology.