Manager, Data Engineering
Lead data engineering and analytics engineering teams to design and own ETL/ELT pipelines, data modeling, quality, and governance. Requires 10+ years data engineering experience including 4+ years managing teams, deep expertise in SQL/Python/modern data stack, and partnering with DS/Product/Eng.
About the job
What You’ll Do
- Design and own ETL/ELT pipelines that move GPU telemetry, product usage, operational data, and customer data from where it lives to where it's useful
- Build and maintain the clean, documented tables that analysts and data scientists actually work from — not raw dumps
- Own data quality end-to-end: schema management, freshness monitoring, lineage tracking, and alerting when something breaks
- Partner with engineering and GTM teams to instrument what isn't already tracked
- Work closely with product, infra, and ML teams, primarily unblocking them
What You’ll Need
- 4+ years of experience managing analytics engineering or data engineering teams, preferably in a scaling startup environment
- 10+ years of total experience in analytics engineering, data engineering, or similar data-focused roles
- Deep expertise in data modeling, ETL pipelines, and data warehouse architecture
- Strong technical foundation with expertise in SQL, Python, and modern data stack tools (dbt, SQLMesh, etc)
- Proven track record of building and leading high-performing teams
- Experience partnering with Data Science, Product, and Engineering leaders to deliver key product metrics and user behavior insights
- Demonstrated ability to balance strategic thinking with hands-on technical leadership
- Strong communication skills with the ability to translate complex technical concepts for diverse audiences
- Experience scaling analytics functions from early stage to maturity in rapidly changing environments
- Track record of establishing data governance, quality standards, and best practices
- A bias for action and urgency, not letting perfect be the enemy of the effective
- A “full-stack mindset”, not hesitating to do what it takes to solve a problem end-to-end
Benefits and Perks
- Comprehensive medical, dental and vision coverage (U.S.)
- Retirement and financial wellness support (U.S.)
- Generous paid time off, plus holidays
- Paid parental leave
- Professional development support
- Wellness and work-from-home stipends
- Flexible work environment
Skills
SQL, Python, dbt, Sqlmesh, ETL, ELT, Data Modeling, Data Warehouse, Data Governance, Data Quality
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