Jobs at Grab (Now Hiring) — 404 open — Page 12

About Grab and Our Workplace

Grab is Southeast Asia's leading superapp. From getting your favourite meals delivered to helping you manage your finances and getting around town hassle-free, we've got your back with everything. In Grab, purpose gives us joy and habits build excellence, while harnessing the power of Technology and AI to deliver the mission of driving Southeast Asia forward by economically empowering everyone, with heart, hunger, honour, and humility.

Get to Know the Team

The Streaming Data team (a.k.a. Coban) ensures seamless and secure real-time access to continuous events or streams, serving as Grab's unified access pattern for real-time data. We build the infrastructure and platform for writing and consuming real-time data, and provide a cost-effective, managed NoOps service for product and data teams across Grab. We partner closely with sister teams in DataTech to provide integrated data platforms that unlock big data innovation every day.

Some examples of the team's work are shared publicly on the Grab Engineering blog:

• Building a self-serve streaming platform for Kafka topics, Flink, CDC pipelines, Kafka Connect, and notebooks (An elegant platform).

• Making Flink deployments safer through platform guardrails and production deployment patterns (Safer deployment of streaming applications).

• Enabling FlinkSQL exploration and productionisation so users can move faster from streaming ideas to running pipelines (The complete stream processing journey on FlinkSQL).

• Improving Flink release confidence with shadow testing (Enhancing Flink deployment with shadow testing).

• Strengthening real-time Kafka data quality with syntactic and semantic stream contracts (Real-time data quality monitoring).

These are examples of the platform thinking this role will continue to advance: taking complex real-time infrastructure problems and turning them into reliable, self-service capabilities for Grab teams.

Get to Know the Role

As a Lead Flink Platform Engineer, you will lead the design, evolution, and operation of Grab's stream processing platform, with Apache Flink as a core compute engine. You will drive medium to large projects across Data Engineering Platforms, mentor senior engineers, and be a technical go-to person for platform architecture, reliability, and production operations. The role is hands-on across Flink, Kafka, AWS cloud infrastructure, Kubernetes, observability, and SRE practices. You will work onsite at Grab Singapore office, One North, and report to the Senior Data Engineering Manager.

Why This Role Matters

• In an agentic world, high-quality real-time signals are becoming even more critical to drive automation, decision-making, and measurable business impact.

• Apache Flink is a critical real-time infrastructure layer for Grab. By making stream processing easier, safer, and more self-serve, this role helps unlock more real-time signals and turn data into business value across Grab. As Grab embraces agentic engineering, we welcome builders with strong data infrastructure experience and a passion for stream processing to join us.

The Critical Tasks You Will Perform

• Lead platform work that makes stream processing easy, reliable, efficient, and secure across Grab through self-serve capabilities built into the platform.
• Design and build abstractions, modules, and libraries that lower the barrier to adopting Flink and reduce operational and security toil for users.
• Improve automation and self-service workflows that allow a small platform team to support many production Flink pipelines at scale.
• Drive technical design discussions, production readiness reviews, incident learning, and long-term architecture improvements.
• Partner with Kafka, data lake, metrics, and data governance platform teams to make real-time data pipelines reliable across the broader Grab data ecosystem.
• Mentor engineers through design reviews, debugging sessions, code reviews, and operational best practices.

What Essential Skills You Will Need

• 5+ years leading teams or projects in software engineering, data engineering, or platform engineering disciplines.
• Experience building and operating stream processing pipelines in production, preferably with Apache Flink or Spark Streaming.
• Strong hands-on engineering experience with Kafka and modern programming languages such as Scala or Java.
• Strong fundamentals in distributed systems, scalable data processing, reliability engineering, and production operations.
• Ability to lead technical design, mentor engineers, communicate trade-offs clearly, and drive projects from design to production.
• Excitement to learn, apply new technologies, and improve platform reliability for many internal users.

The nice-to-haves:

• Experience with Kafka Connect, Kubernetes, Go, GitLab CI, AWS, or Terraform.
• Experience building reusable platform abstractions, SDKs, deployment tooling, or self-service workflows.
• Experience operating Apache Flink in production, including high availability, checkpointing, safe deployments, and incident response.
• Experience with a data warehouse or data lake ecosystem such as Spark, Parquet, Iceberg, Delta, or Hudi.

Life at Grab

We care about your well-being at Grab, here are some of the global benefits we offer:

• We have your back with Term Life Insurance and comprehensive Medical Insurance.
• With GrabFlex, create a benefits package that suits your needs and aspirations.
• Celebrate moments that matter in life with loved ones through Parental and Birthday leave, and give back to your communities through Love-all-Serve-all (LASA) volunteering leave
• We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges.
• Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours

What We Stand For at Grab

We are committed to building an inclusive and equitable workplace that enables diverse Grabbers to grow and perform at their best. As an equal opportunity employer, we consider all candidates fairly and equally regardless of nationality, ethnicity, religion, age, gender identity, sexual orientation, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.