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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:
Minimum 3 years of experience in managing top-tier engineering teams
5+ years experience building data infrastructure systems such as Apache Spark™ or database internals.
A passion for database systems, storage systems, distributed systems, or performance optimization
Experience working with product management, and directly with customers; ability to understand customer needs.
Can ensure the team builds high quality and reliable infrastructure services. Experience being responsible for testing, quality, and Service Level Agreements of a product. Experience building and managing teams in a complex technical domain, such as on distributed data systems or database internals.
Expertise in attracting, hiring and coaching engineers, who will meet the Databricks hiring standards. Experience up-leveling teams via hiring top-notch talent and growing existing team members.
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 compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Skills Required
- Minimum 3 years of experience in managing top-tier engineering teams
- 5+ years experience building data infrastructure systems
- Ability to understand customer needs
- Experience managing technical debt
- Expertise in attracting and hiring engineers
Databricks Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.
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Equity Value & Accessibility — Equity grants and RSUs are a major part of total compensation and are highlighted for meaningful upside potential. Stock-based awards and refreshers contribute to strong overall pay positioning across senior technical and go-to-market roles.
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Healthcare Strength — Medical, dental, and vision coverage are complemented by mental-health resources, an EAP, and wellness reimbursements. Health benefits are consistently framed as comprehensive and competitive.
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Parental & Family Support — Paid parental leave for all parents, fertility support, and backup care options provide tangible assistance for family needs. Hybrid work norms and team-day structure further ease coordination for caregivers.
Databricks Insights
What We Do
As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.
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