Lead Data Engineer, GrabX (Experimentation & Config Management)

Get to Know the Team
GrabX is Grabs mission-critical Configuration Management and Experimentation platform. We empower every product team at Grab to ship features safely and make data-driven decisions through A/B testing and automated experiment analysis. The platform handles the massive scale of Grabs traffic managing real-time configurations for millions of concurrent users and processing petabytes of data to provide automated statistically rigorous insights. Our goal is to minimize the time to insight for engineers and product managers ensuring that every feature launched at Grab is backed by high-fidelity data.

Get to Know the Role

We are looking for a Lead Data Engineer for the GrabX team. This position focuses heavily on the data backbone of experimentation leading the design of high-throughput data pipelines that feed our automated analysis engines. You will report to an Engineering Manager in Singapore and work onsite at the Grab Malaysia Office

The technical stack includes:

• Data Processing & Storage: Apache Flink Apache Spark Trino StarRocks and Delta Lake.
• Online Serving & Config: Golang AWS infrastructure Redis ScyllaDB and DynamoDB.
• Infrastructure: Kubernetes Terraform and CI/CD for data workloads.

The Critical Tasks You Will Perform

• Design and build robust batch and real-time data pipelines to process billions of experiment events daily for automated analysis.
• Develop highly efficient Spark or Flink jobs to calculate complex business metrics and statistical significance at scale.
• Implement rigorous data validation and monitoring frameworks to ensure experiment results are accurate and trustworthy.
• Lead the transition of our data architecture toward a centralized Metric Store model for seamless reuse across product groups.
• Mentor a team of engineers while driving best practices in data modeling and system design for data-heavy applications.
• Collaborate with Data Scientists to automate hypothesis testing and anomaly detection within the experimentation lifecycle.

Qualifications :

What Essential Skills You Will Need

• Minimum of 7 years of experience in Data Engineering or Software Engineering with a strong focus on data-heavy systems.
• Expert-level proficiency in at least one of the following: Scala Go or Python.
• Extensive experience building large-scale data processing systems using Apache Spark or Apache Flink.
• Strong understanding of OLAP database technologies such as StarRocks ClickHouse or Trino.
• Proven track record of leading engineering teams and managing technical trade-offs in high-load low-latency environments.
• Deep knowledge of data modeling data warehousing and managing distributed systems at petabyte scale.
• Strong English communication skills with experience working in regional or global environments.

A big plus if you have:

• Experience building internal experimentation platforms or automated A/B testing frameworks.
• Proficiency in CI/CD tools AWS Terraform and Kubernetes for data infrastructure.
• Familiarity with statistical concepts used in experimentation such as p-values and confidence intervals.

Additional Information :

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 lifes challenges.
• Balancing personal commitments and lifes 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.

Remote Work :

No

Employment Type :

Full-time