Lead Data Engineer, Metrics Platform

Get to Know the Team

The Metrics Platform team is a team within Grab's Data Technology organization, with members across Singapore, Indonesia, Thailand, Vietnam and Malaysia. We build the central platform for metrics that enables Grabbers across the company to define, serve, discover, and consume trusted business and product metrics at scale. Our platform is an important foundational layer for Grab's AI-powered data ecosystem. By making metrics reliable, reusable, discoverable, and served across teams, we help power better analytics, experimentation, automation, and AI-assisted data workflows across Grab.

Get to Know the Role

The Lead Data Engineer role in the Metrics Platform team is a hybrid data and software engineering role. You will be an important member of the team that designs, builds, and operates Grab's metrics platform across metric serving, ingestion, metadata, query generation, platform APIs and several cross platform integrations. You will be responsible from technical design and implementation to rollout and production operations. You will contribute hands-on while guiding engineering quality through design reviews, operational improvements, and collaboration with partner teams.

You will report to the Senior Data Engineering Manager and will be based onsite at our office in Petaling Jaya.

The Critical Tasks You Will Perform

• You will lead major platform initiatives that help teams model, publish, discover, and consume trusted metrics and data products across Grab.
• You will shape technical direction with the engineering manager and team, balancing user needs, reliability, scalability, cost, and delivery constraints.
• You will design and implement platform services, APIs, metadata systems, query generation, and tooling, establishing patterns that other engineers can extend and operate.
• You will turn ambiguous requirements into clear technical designs and delivery plans, coordinating dependencies and rollout decisions across teams.
• You will lead technical collaboration with engineering, analytics, and data science teams to onboard use cases and establish reusable integration patterns.
• You will strengthen engineering standards through design and code reviews, mentoring, testing practices, documentation, and self-serve workflows.
• You will guide the operation and evolution of metrics serving infrastructure, including Apache Pinot, StarRocks, data ingestion systems and pipelines, and related cloud services.
• You will lead investigations into reliability, performance, and correctness issues, driving improvements that prevent recurrence.
• You will guide responsible use of AI-powered tools, ensuring generated code, queries, and outputs meet engineering and data quality standards.
• You will use AI-powered coding, analytics, and data engineering tools responsibly to accelerate development, debugging, documentation, testing, and data investigation.

Function: Engineering
Experience Level: Associate