Data Product Owner
- Frame business needs as data products : work directly with C-level executives and business teams to understand their objectives and translate them into actionable use cases.
- Prioritize and plan : define the roadmap, break it down into deliverables, and ensure the team stays focused on what drives the most value.
- Explore and model the data yourself : query datasets in SQL, analyze raw tables, and design the data models needed to answer key business questions.
- Shape data structures with engineers : collaborate closely with data engineers to design pipelines, build scalable data models, and ensure the right level of granularity for future use cases.
- Work as part of a close-knit team : you'll have the support of experienced data engineers, and senior leaders who work with you to remove blockers and deliver impact.
- Drive adoption : make sure the products you build are actually used, whether it's a dashboard, a data pipeline, or a reporting layer, by training and supporting business teams.
- Test and iterate : work with a hypothesis-driven approach, refining both the business framing and the data model as you learn.
What We're Looking For We're looking for a Data Product Owner who thrives at the intersection of business and data. Someone who can translate a business's objective into a roadmap, prioritize ruthlessly, and work hand-in-hand with our data engineers to deliver. You'll likely have 2-4 years of experience in a data-related role (consulting, analytics, product, BI...). The exact title matters less than your ability to navigate both business conversations and data problems with confidence. We're not after a "scrum master" or a pure analyst. We need someone who can:
- Understand business problems and shape them into data products.
- Own the delivery end-to-end: from framing to design to adoption.
- Navigate mid-sized to large company environments with empathy (no big-corporate layers, but you need to be comfortable with hands-on complexity).
- Be comfortable getting close to the data: write (or learn to write) SQL queries, dig into raw tables, challenge assumptions with facts, and understand the technologies we use.
- Work with a hypothesis-driven mindset, framing questions and testing solutions quickly to converge on what delivers the most impact.
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