Data Engineering Manager

Overview

Data Engineering Manager responsible for supervising a local data engineering pod across data-platform and analytics/reporting workstreams.

What you'll do

• Supervise and support the local data engineering pod across platform and analytics/reporting.
• Manage team capacity, lead hiring, and define team charters for the data-platform roadmap.
• Drive operational discipline for a distributed org, including onboarding and on-call/incident response processes.
• Plan and execute multi-quarter, interdependent initiatives (e.g., lakehouse re-architecture, late-impression pipeline, CI/CD automation).
• Refine engineering practices and technical standards (code quality, IaC, deployment automation, observability, cost optimization).
• Stay hands-on in implementation across pipeline design, product feature delivery, reviews, tech debt, and production troubleshooting.
• Own production responsibilities including monitoring/alerts, on-call support, incident management, and postmortems.

What you'll need

• Minimum 8 years of experience in Data Engineering with leadership in technical settings.
• Expert knowledge of Python and SQL.
• Deep hands-on experience with distributed data processing and streaming using Apache Spark/Spark Streaming and Apache Flink.
• Strong experience operating high-throughput event streaming and messaging with Apache Kafka.
• Proficiency with Google Cloud data stack (BigQuery, GKE, GCS, Dataflow/Vertex AI) and Terraform.
• Experience building and operating CI/CD for data pipelines (e.g., ArgoCD, Docker/containerized deployments).
• Working knowledge of lakehouse/open table formats (e.g., Iceberg/Delta) and real-time vs batch trade-offs.

Details

• Location: Bangalore, India.
• Estimated hands-on time: 50–70%.