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Sr. Product Manager, AI-Accelerated Tables

Databricks

View all jobs at Databricks

Location: California

Category: Product

Domain: AI

Experience Level: Mid Level

Compensation: $115,400—$204,200

Posted 8 months ago

Job Description

As the Product Manager on the team, you’ll own the full portfolio of our AI-accelerated table offerings, including Predictive I/O, Predictive Optimization, Liquid clustering and our future facing roadmap. You’ll manage their success end-to-end. You’ll engage with top customers to identify where they spend the most time configuring and tuning their table. You’ll set the vision for how we can apply AI to automate away this toil and partner closely with engineering to make these capabilities a reality. You’ll identify and address sharp edges and roadblocks which prevent adoption. And you’ll work with marketing and our field to take the capabilities to market.

The impact you will have:

Drive the vision of AI-accelerated tables, making customers’ data performant and easy-to-use out of the box

Conduct customer research and data science to identify the largest AI optimization opportunities

Work closely with customers to understand their data management needs and pain points.

Drive uptake and adoption of AI-accelerated offerings by defining and driving OKRs, addressing adoption blockers, and iterating on capabilities to make them more compelling

Collaborate with engineering to define and deliver the next generation of AI-accelerated offerings

Drive launches with the field and product marketing through blog posts, release notes, webinars and internal enablement

We Expect You To

5+ years of product management and related experience with enterprise or SaaS products

Experience with bringing new products to market and growing their adoption

Experience with conveying ideas clearly and concisely

Bachelor’s degree in Computer Science or similar field

Developer empathy, e.g. worked in developer-facing products or similar

Strong data analysis and operationalization skills (SQL & Python, rollups, building operational dashboards)

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