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Ellevation Education is seeking a Senior Product Manager to own the data ingest domain—the extract, transform, and load (ETL) architecture that powers the platform's data operations and downstream product workflows.
You will join a cross-functional DevPro team (product, design, engineering) that operates with high autonomy and accountability. The role emphasizes outcomes over output: you'll engage users early, validate hypotheses through research and prototyping, and iterate rapidly. The company uses Shape Up methodology and expects product managers to leverage AI tools (Claude, etc.) as on-demand collaborators to explore ideas, stress-test assumptions, and move from problem to prototype faster.
In your first month, you'll build an independent, evidence-grounded understanding of the data ingest ecosystem, data operations processes, and downstream workflows. You'll establish trust with your DevPro team, Data Operations, and cross-functional stakeholders, operating as a peer from day one.
By three months, you'll develop meaningful expertise in your domain—fluency in ETL architecture, troubleshooting, and using data to inform product perspectives. You'll become an active contributor on product initiatives, taking on user research, data analysis, problem framing, and enablement.
At six months, you'll take full accountability for product success from idea to launch: driving product learning through user research and data analysis, leading the team in working backwards from outcomes, and owning go-to-market delivery. You'll develop a clear point of view on opportunities in the data ingest space and build influence with senior stakeholders.
By 12 months, you'll use your expertise to drive the team forward, anticipate tradeoffs, and identify new opportunities for ingest investments. You'll have a demonstrated track record of transforming ambiguous technical and organizational problems into successful outcomes.
The role requires in-person presence in Boston at least two days per month, plus company offsites. Boston-area residency is strongly preferred.
REQUIREMENTS:
- 5–8 years relevant experience, including at least 3 years in product management. Related experience in data engineering, business intelligence, or analytics is welcome.
- Passionate about data and data workflows. Experience with ETL data pipelines, data mapping and transformation, and comfort troubleshooting how data flows affect downstream users.
- Demonstrated success leading highly technical ETL teams with deep interest in how systems work. You dig into technical concepts, explore systems impact, and weigh tradeoffs.
- Evidence-driven and curious. Genuine interest in understanding problems faced by internal users and customers. Leverage direct user discovery and can run data analyses yourself to ground problem framing.
- AI-fluent. You've used AI tools for data analysis, prototyping, or documentation and have a point of view on where they help in this domain.
- Effective in cross-functional teams. Work well with diverse people and eager to collaborate daily with Product, Engineering, and Data Operations stakeholders.
- Experience leading and managing senior cross-functional stakeholders. Articulate the "why" behind decisions, translate technical concepts for non-technical audiences, and treat enablement as core to the job.
- Organized and dependable. Follow through on commitments, flag risks early, and deliver reliably under operational pressure (e.g., Back to School season).
- Strong learner. Actively learn from experience, solicit and apply feedback quickly, and articulate how your thinking has changed.
NICE TO HAVES:
- Experience in education, working with multilingual learner communities, or meaningful connection to the mission.
- Capable of querying data (SQL or similar) to investigate problems or support decisions; comfort with cloud data warehouses like Snowflake.
- Basic data modeling familiarity (schemas, relationships, identifiers, downstream dependencies).
- Experience with SIS (student information system) data, interoperability standards (OneRoster), or hands-on experience with rostering platforms (Clever, ClassLink).
- Exposure to internal tooling in enterprise B2B SaaS where some "customers" are internal operations teams.
- Familiarity with product discovery methods: user interviews, lightweight prototyping, structured experimentation.
