Manage and grow a team of 5+ data engineers
Drive architectural decisions across the platform and ensure systems are built for high availability, scalability, and security
Guide the team through complex technical challenges
Lead efforts to improve query performance and platform efficiency
Collaborate with product managers and architects to define and deliver the data platform roadmap
Own the operational posture of the platform — monitoring, alerting, incident response, and on-call rotation management
Define engineering best practices and champion shift-left data governance

8+ years in data or software engineering, with 2+ years managing engineering teams of 5 or more
Proven experience designing complex data systems, with specific expertise in Semantic Layering and Data Sharing at enterprise scale
Deep, hands-on experience with dbt and semantic models (eg MetricFlow) — including designing and scaling semantic models in production
Strong proficiency with Snowflake and SQL
Experience with Spark, Python, and Snowpark is a plus
Hands-on experience with technologies such as Cursor, Claude CLI/Code, Kibana, and Airflow
Experience owning on-call processes, managing incidents, and defining operational metrics
Solid command of CI/CD practices (e.g., GitHub Actions) and data observability tooling such as DataDog or Monte Carlo
Strong written and verbal communication skills

Engineering Manager, Data Platform

Key skills