Sr. Product Manager, Data Engineering
Databricks · San Francisco, California · Product · listed August 11, 2022
The shape of it
Seniority
Manager
Experience asked
5+ years
Where
Not stated
Stated pay
$115,400 – $204,200 USD
Requirements listed
7
Length
721 words
In the posting’s own words
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.
What it asks for · 7
- 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.
What the job covers
- 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.
Tools and skills named
Data
- Databricks4×
- Data pipelines
- Data warehouse
Product & design
- Product management4×
- Roadmap
Go to market
- Go-to-market
- Partnerships
- SaaS
Models & research
- Machine learning
Ways of working
- Cross-functional
Words the posting leans on
- data18×
- product15×
- data engineering6×
- product management4×
- development3×
- background2×
- business2×
- customers2×
- databrick2×
- deep2×
- drive2×
- engineering foundational2×
- enterprise2×
- experience2×
- field2×
- impact2×
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