Data Engineering Manager
On-site · Bengaluru, Karnataka, India
Job Summary
Data Engineering Manager overseeing a distributed data engineering pod (data-platform and analytics/reporting) with hands-on involvement (50-70%) in designing pipelines and features. Responsibilities include managing team capacity, hiring backfills, defining team charters, and fostering a high-performance culture across distributed teams (Bangalore and EU). Lead multi-quarter initiatives (e.g., data lakehouse re-architecture with Apache Flink on GKE, CTV late-impression pipeline, CI/CD automation with ArgoCD), ensure code quality and infrastructure-as-code practices, and optimize costs. Collaborate with Product Management, Backend Engineering, Data Science, and Analytics to align the platform roadmap with business objectives, and handle production responsibilities including monitoring, on-call, incident response, and postmortems. Independently design maintainable and scalable data systems for complex, high-throughput streaming and batch pipelines while managing data infrastructure costs.
Required Qualifications
- Minimum of 8 years of Data Engineering experience with leadership in technical settings
- AdTech industry expertise strongly preferred
- Expert knowledge of Python and SQL
- Deep experience with distributed data processing and streaming: Apache Spark / Spark Streaming and Apache Flink
- Strong experience 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 (ArgoCD, Docker)
- Familiarity with lakehouse/open table formats (Iceberg/Delta) and trade-offs between real-time and batch architectures
- Familiarity with analytics/OLAP and BI tooling (Looker, Rill/Turnilo) and dimensional data modeling
- Strong capability to design maintainable, scalable data systems for high-throughput streaming and batch pipelines
- Experience with monitoring, on-call support, incident management and postmortems
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