Strategic Overview
Sr. Product Manager, Data Engineering at Databricks is a product opportunity centered on the specialist responsibilities and outcomes described in the employer's listing.
The published role emphasizes work such as Lead product management for one of the fastest growing products and businesses at Databricks Define, shape, and drive the future of data processing, data applications, and data pipelines.
The role is listed for San Francisco, California with the working arrangement published with the role, giving candidates the practical context needed to assess fit before applying.
Key information at a glance
About This Role
P-8
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.
Data Engineering is foundational and among the largest scale workloads on the Databrick Data Intelligence Platform. We are reinventing Data Engineering with Lakeflow - a unified product and experience for simple data ingestion, declarative data transformation, and real-time streaming. In this role, you will lead product management for a core Lakeflow product area. You will own and drive all aspects of product…
Key Responsibilities & Objectives
- Lead product management for one of the fastest growing products and businesses at Databricks
- Define, shape, and drive the future of data processing, data applications, and data pipelines
- Own the full life cycle of product development from ideation to requirements, development, pricing, launch, and go-to-market.
- Analytical skills to make data-driven decisions (e.g. analyze product usage)
Required Qualifications & Candidate Blueprint
- Develop and deepen understanding of and expertise in Data Engineering, a foundational domain in the data and AI industry
- 5+ years of product management and related experience with enterprise or SaaS products.
- Educational or professional background in computer science or related engineering fields.
Salary & Benefits
Published compensation: $115,400 – $204,200 USD
Salary Benchmark
This role’s published compensation is compared with current employer-disclosed salary ranges for the same role at the Senior level in the same currency.
Benchmark uses active employer job postings in our database and excludes this listing. It is not a third-party salary estimate, and currencies are not converted.
Full Job Description
The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.
P-8
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.
Data Engineering is foundational and among the largest scale workloads on the Databrick Data Intelligence Platform. We are reinventing Data Engineering with Lakeflow - a unified product and experience for simple data ingestion, declarative data transformation, and real-time streaming. In this role, you will lead product management for a core Lakeflow product area. You will own and drive all aspects of product management including vision, strategy, roadmap, execution, and go-to-marketing. In addition, you will partner closely with various Databricks product teams to enable Data Engineering for the overall Databrick product portfolio including data science, data warehousing, business intelligence, and machine learning products.
The impact you will have
- Lead product management for one of the fastest growing products and businesses at Databricks
- Make company wide impact by driving Data Engineering across the Databricks product portfolio
- Develop and deepen understanding of and expertise in Data Engineering, a foundational domain in the data and AI industry
- Define, shape, and drive the future of data processing, data applications, and data pipelines
- Own the full life cycle of product development from ideation to requirements, development, pricing, launch, and go-to-market.
What We Look For
- 5+ years of product management and related experience with enterprise or SaaS products.
- Educational or professional background in computer science or related engineering fields.
- Ability to partner with senior technical leaders from Engineering, while going deep on technical concepts.
- Track record of delivering products with cross-functional teams common to enterprise software industry (field engineering, sales, marketing, partnerships, etc.)
- Analytical skills to make data-driven decisions (e.g. analyze product usage)
- Excellent communication skills to clearly and concisely communicate complex topics to diverse stakeholders (engineers, customers, etc.) in written and verbal form
- A background in Data Engineering is a plus but not required.
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.
Editor’s Market Perspective (Our Custom Analysis)
Why This Position Matters
This product opening is a useful opportunity for candidates whose experience matches the role-specific capabilities named in the listing. Its strongest career signal is the scope of the work itself — particularly Lead product management for one of the fastest growing products and businesses at Databricks — rather than a generic title alone.
Resume & Application Strategy
For the application, mirror the employer's language where it truthfully matches your background: foreground the role-specific capabilities named in the listing, quantify outcomes from comparable work, and place the most relevant experience near the top of the resume. If the listing specifies tools, platforms, leadership scope, or domain experience, use those exact terms in context instead of presenting an unrelated keyword list.
We organize source-provided information into this independent job-seeker overview. Compensation is shown only when the source provides it; the official listing remains the authority for current requirements and application instructions.