Databricks · posted 33w ago
P-1110
At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business.
We are the Lakeflow Engineering team, responsible for Databricks ETL product line: Jobs, Spark Declarative Pipelines, and Genie Code for Data Engineering. We run one of the world's biggest (if not the biggest) data engineering platforms - responsible for processing exabytes of data daily for tens of thousands of customers.
We're seeking a dedicated Engineering Leader to spearhead the Pipelines Engine engineering team. The team is responsible for building next generation Runtime ETL features and ensuring that Lakeflow Pipelines has state of art performance for ETL workloads. You will also spearhead the Agentic Data Engineering infrastructure, by building the next generation engine to power agentic pipeline authoring, execution and maintenance.
The main responsibilities include:
You will lead an engineering team building the next-generation ETL features for the Databricks Lakeflow platform.
You will oversee sustained recruitment of top-tier talent, and upskilling talent on the team.
You will build processes to implement product vision and strategy, according to organizational goals and priorities.
You will build software that is not just high quality but easy to operate.
You will manage technical debt, including long-term technical architecture decisions and balance product roadmap.
What we look for:
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensa