P-1701
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 + AI platform so our customers can use deep data insights to improve their business. Founded by engineers, we’re customer obsessed, leaping at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.
As an Engineering Manager on CustomerLake, you will lead the team building Profile Agents, shaping the product, architecture, and engineering foundation behind Databricks’ Customer 360 platform.
CustomerLake is Databricks' new Agentic CDP, launched at Data + AI Summit 2026. This is our first move into agentic business applications, offering the data foundation of Marketing built natively into the Databricks Lakehouse. Early traction for this new product has been outstanding.
Profile Agents are a key foundation of this product. Building a trustworthy Customer360 has traditionally meant multi-year integration projects and seven or eight figures in professional services just to get a usable golden record. Profile Agents generate the pipelines, matching logic, and identity resolution needed to produce a Customer 360.
The product is early and still being defined, so you'll have real say over the product vision, architecture and how the team operates and scales.
The impact you will have
- Own delivery for Profile Agents, from identity resolution and agentic pipeline generation through to production-quality Customer 360 outputs
- Hire and grow a small, senior team, and build the foundation it scales from as the product moves out of private preview
- Help set technical direction with product and the VP of Engineering, since much of what "good" looks like here is still undefined
- Build the quality bar for agent-generated pipelines: where agents act autonomously, where they need human review, and how we validate correctness against customer data
- Work directly with customers and design partners to help turn their Customer360 problems into engineering priorities
- You will have lots of room for growth by joining one of the fastest growing teams in one of the fastest growing Data + AI companies in the world
What we look for
- 3+ years of engineering management experience leading high-performing engineering teams
- 8+ years of experience building and operating production data or distributed systems, with the hands-on depth to set a technical bar for the team
- Experience building or leading teams that ship data engineering products such as ETL, MDM, or data quality tooling, and an understanding of why Customer 360 projects are typically so expensive and slow
- Hands-on experience applying agents or LLMs to data engineering problems like matching, entity resolution, or pipeline generation, with a clear view on where agent autonomy helps versus where humans need to stay in the loop
- Genuine passion and prior experience taking a product from 0 to 1: comfortable defining process and architecture with no existing playbook
- Ideally, some understanding of how customer data is used downstream in marketing, sales, and service
- A track record scaling complex data services to thousands of enterprise customers, including the reliability and governance maturity that requires
- Experience managing multiple teams or other managers is a strong plus
- BS or higher in Computer Science or a related field, or equivalent experience
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 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
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.
Applicant Privacy Notice
Skills Required
- 3+ years of engineering management experience leading high-performing engineering teams
- 8+ years building and operating production data or distributed systems
- Experience building or leading teams that ship data engineering products such as ETL, MDM, or data quality tooling
- Hands-on experience applying agents or LLMs to data engineering problems (matching, entity resolution, pipeline generation)
- Experience taking a product from 0 to 1, defining process and architecture without an existing playbook
- Track record scaling complex data services to thousands of enterprise customers, with reliability and governance maturity
- BS in Computer Science or related field, or equivalent experience
- Understanding of how customer data is used in marketing, sales, and service
- Experience managing multiple teams or other managers
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 are a meaningful part of offers, and periodic tender opportunities and secondary options have made private equity more tangible for many employees. This perceived upside contributes to strong total-compensation sentiment in key roles.
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Healthcare Strength — Comprehensive medical, dental, and vision coverage is paired with mental‑health resources and wellness reimbursements, indicating a robust health package. Multiple summaries highlight broad coverage that employees can practically use.
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Leave & Time Off Breadth — Generous PTO, paid holidays/sick time, and fully paid parental leave are frequently described, with hybrid/remote flexibility common in the U.S. These policies expand time‑off accessibility across different life stages.
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.
