Sr. Product Manager, Data Engineering

Posted 7 Hours Ago
Be an Early Applicant
San Francisco, CA
115K-204K Annually
Senior level
Big Data • Machine Learning • Software • Analytics • Big Data Analytics
The Role
The Sr. Product Manager for Data Engineering at Databricks will lead product management efforts, driving product vision, strategy, and execution for core Data Engineering areas. Responsibilities include managing the product lifecycle, collaborating with engineering teams, and utilizing analytical skills for decision-making.
Summary Generated by Built In

RDQ425R28

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 one of the fastest growing product areas of the Databrick Lakehouse platform. We are innovating towards simple data ingestion, real-time stream processing, and a declarative framework and experience for ETL. In this role, you will lead product management for a core Data Engineering 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, and machine learning products.

The impact you will have

  • Lead product management for one of the fastest growing 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 base 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 utilizes 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.


Zone 1 Pay Range

$115,400$204,200 USD

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, please visit https://www.mybenefitsnow.com/databricks. 

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.

The Company
New York, NY
2,200 Employees
On-site Workplace
Year Founded: 2013

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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