Lead Data Infrastructure Engineer

📋 Description

• Design, build and operate batch and streaming pipelines for robot telemetry, sensor recordings
• Implement data quality and validation frameworks — schema enforcement, completeness and freshness
• Build observability for the pipelines themselves: throughput, lag, cost, failure modes and clear
• Build and maintain dashboards and curated, self-serve datasets for engineering, data science and
• Integrate robotics data and ML workloads onto Grab's central data and ML platforms — lakehouse
• Design storage, indexing and retention for high-volume sensor data (ROS 2 / MCAP recordings, video

🎯 Requirements

• Strong Python and SQL, with the ability to write production-grade data services rather than one-off
• Hands-on experience building and operating both batch and streaming pipelines (Spark, Flink, Kafka
• Workflow orchestration at production scale (Airflow, Dagster, Argo Workflows or similar).
• Data warehouse and lakehouse experience: open table formats (Iceberg, Delta, Hudi), partitioning
• Demonstrated ownership of data quality: validation frameworks, data contracts, tests, and alerting
• Experience with observability and dashboarding tooling (Prometheus/Grafana, Superset, Tableau or

🎁 Benefits

• Term Life Insurance and comprehensive Medical Insurance.
• GrabFlex: create a benefits package that suits your needs and aspirations.
• Parental and Birthday leave, and Love-all-Serve-all (LASA) volunteering leave.
• Grabber Assistance Programme for guidance and support through life's challenges.
• FlexWork arrangements such as differentiated hours.