Sr. Engineering Manager (Data Infrastructure): Leading the Pipelines Engine team to build next-generation Runtime ETL features and Agentic Data Engineering infrastructure with an accent on performance and scalability. Focus on designing distributed data systems, managing technical architecture for exabyte-scale processing, and scaling top-tier engineering talent.
Location: Mountain View, California or San Francisco, California
Salary: $228,600 — $317,233 USD
Company
Databricks is a data and AI company providing a Data Intelligence Platform to unify data, analytics, and AI for over 10,000 organizations worldwide.
What you will do
Lead the engineering team building next-generation ETL features for the Databricks Lakeflow platform.
Spearhead Agentic Data Engineering infrastructure to power agentic pipeline authoring, execution, and maintenance.
Oversee recruitment, hiring, and upskilling of top-tier engineering talent.
Develop processes to implement product vision and strategy aligned with organizational goals and priorities.
Manage long-term technical architecture decisions and balance the product roadmap against technical debt.
Ensure the delivery of high-quality software that is reliable and easy to operate.
Requirements
Minimum 3 years of experience in managing top-tier engineering teams.
5+ years of experience building data infrastructure systems (e.g., Apache Spark or database internals).
Deep passion for and expertise in distributed systems, storage systems, or performance optimization.
Proven experience in attracting, hiring, and coaching engineers to meet high hiring standards.
Experience collaborating with product management and customers to translate business needs into technical requirements.
Expertise in managing SLAs, testing, and quality for complex infrastructure services.
Culture & Benefits
Comprehensive benefits and perks tailored to the specific region.
Opportunity to work on one of the world's largest data engineering platforms processing exabytes of data daily.
Inclusive culture committed to diversity, equal employment opportunity, and fostering an environment where everyone can excel.
Direct impact on the development of foundational AI and data infrastructure.
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