Engineering Manager

Role summary
This position is responsible for leading a data engineering team within the OpenBlue Data Platform. The Engineering Manager is accountable for people leadership, L3 support, and delivery, and continues to contribute hands-on to data pipeline and platform engineering.
Location: Pune, India
People leadership
Lead, coach, and grow a team of engineers; run 1:1s, goal setting, performance reviews
Hire and onboard engineers to support team growth and evolving business needs
Build a team culture of ownership, quality, and cross-team collaboration (US/India)
L3 support & operational excellence
Own L3 defect triage, prioritization, and resolution across SIT, UAT, and production
Drive RCA and tech-debt reduction to lower recurring defect volume
Coordinate release/deployment support across regions (NA, Europe, UAE, APAC)
Define and track support metrics (MTTR, defect aging, escape rate)
Delivery & planning
Partner with product and architects in PI planning; translate requirements into sprint plans
Manage team capacity, dependencies, and risk; report status to leadership
Ensure Jira hygiene and predictable sprint delivery
Hands-on data engineering
Design, build, and optimize batch and streaming pipelines (Kafka, Flink, Spark)
Contribute to lakehouse and storage work (Iceberg, Trino, Snowflake, HBase, Postgres/TimescaleDB)
Review code and set engineering standards for data quality, testing, observability
Deliver feature work, e.g. aggregation, compliance, and monitoring capabilities
Qualifications
8+ yrs software/data engineering; 1–2+ yrs leading engineers (formal or tech lead)
Strong in Java/Scala/.NET/SQL and distributed data processing
Proven L3/production support and RCA experience
Familiar with Kubernetes, CI/CD, Azure
Agile/SAFe PI planning experience
Nice to have
Building/IoT/timeseries domain experience
Open items to confirm
☐ Location: Pune?
☐ Hands-on split: ~30–40%?
☐ Years-of-experience bar
☐ Team size / direct reports in scope

Skills
Java, .NET, Kafka, Azure, Kubernetes, CI/CD, SQL, PostgreSQL, Snowflake, Apache Spark