Lead Platform Engineer, Flink

GrabTaxi Holdings Pte. Ltd.; Singapore; On-site; SGD 180,000 - 240,000; Full time

Benefits offered by this job

Term Life Insurance

Medical Insurance

GrabFlex

Parental leave

Birthday leave

LASA volunteering

Grabber Assistance

FlexWork

Job summary

GrabTaxi Holdings Pte. Ltd. in Singapore is seeking a Lead Flink Platform Engineer to design, evolve, and operate Grab's streaming platform using Apache Flink, Kafka, and AWS.

You will mentor engineers, drive architecture across data engineering platforms, and own production readiness and incident learning. This role is onsite at Grab Singapore One North and reports to the Senior Data Engineering Manager.

Qualifications

• 5+ years leading teams or projects in software/data/platform engineering.
• 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.

Responsibilities

• 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.

Skills

Leading teams

Stream processing

Kafka

Scala/Java

Distributed systems

Technical design

Mentoring engineers

Tools

Kubernetes

AWS

Terraform

GitLab CI

Job description

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.

• 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.

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.