Senior Product Manager

Team: Product

Location: Boston, MA or Remote

Commitment: Full Time

Workplace Type: remote

Product Culture

Product Culture

We are organized into small, durable product teams that develop solutions in specific domains. Our teams are cross-functional — product, design, and engineering work so closely together that we call ourselves DevPro and rarely meet in functional silos. We focus on outcomes over output, which means we engage users early, validate hypotheses through research and prototyping, and iterate rapidly toward high-confidence solutions.

While we work in separate teams, we prioritize integration and consistency of our solutions, meaning consistency isn’t a nice-to-have, it’s a critical part of our end goal.

We expect AI tools like Claude Cowork and Claude Code to be central to product managers’’ workflows — as on-demand collaborators that help explore ideas quickly, stress-test assumptions, and move from problem to prototype faster. This is not about replacing PM judgment; it is about using AI to expand what is possible within the constraints of appetite and scope.

We value product managers who think strategically and are able to look at problems from multiple angles, weigh tradeoffs, and articulate how a solution meets the needs of both users and the business. We celebrate accountability to outcomes: building to learn, raising risks early, adapting quickly when the evidence points a new direction, and rapidly delivering products that create real value for educators and students.

1 month

• Build an independent, evidence-grounded read on the key challenges and business context in your domain, including the data ingest ecosystem, data operations processes, and downstream product workflows, with attention to in-progress work and team priorities.

• Establish high-trust relationships with your DevPro team, Data Operations, and cross-functional stakeholders across R&D and the business — operating as a peer from day one.

• Understand Ellevations approach to product development, including our Shape Up methodology and how we think about discovery, appetite, and scope.

3 months

• Develop meaningful expertise in your domain, showing fluency in the product’s extract / transform / load architecture, troubleshooting product questions, and using relevant data to inform product perspectives. Understand the users you serve and the problems that matter most to them, and how all of it matters to the business.

• Become an active contributor toward your product team’s initiatives, taking on user research, data analysis, problem framing, and enablement efforts.

• Continue building influential, high trust relationships across the organization, helping stakeholders feel heard and informed and creating opportunities for them to plug into the work.

6 months

• Take full accountability for the success of the product from idea to launch:

  • Proactively drive product learning: set ambitious learning objectives and tackle them with user research, data analysis, and identifying hypotheses and testable product increments.

  • Lead the team in working backwards from outcomes by raising risks and dependencies and driving execution. 

  • Drive go-to-market delivery as a first-class part of the job: internal teams are trained and adopting each release.

  • Develop a clear, articulated point of view on opportunities in the problem space you own. Contribute to shaping product pitches with leadership. 

  • Build and sustain influence with senior stakeholders, evangelizing our product bets, surfacing tradeoffs, and developing alignment.

12 months

• Use the expertise and context you have built over the past year to drive the team forward, anticipate tradeoffs, and identify new opportunities for future ingest investments to advance our broader business goals.

• Develop a demonstrated track record of transforming ambiguous problems in the data ingest domain - whether technical or organizational - into successful outcomes for users and the business.

• Influence and elevate others across the organization, collaborating to solve problems and raising the bar for how Product approaches technically complex domains.

About You

• 5-8 years relevant experience, including at least 3 years in product management. Related experience welcome in data engineering, business intelligence, or analytics.

• Passionate about data and data workflows. Experience with ETL data pipelines, data mapping and transformation, and comfortable digging in to troubleshoot or understand how data flows affects downstream users.

• Demonstrated success leading highly technical ETL teams, with a deep interest in how things work. You dig in to understand technical concepts, explore systems impact, and weigh tradeoffs.

• Evidence-driven and curious. You are genuinely interested in understanding the problems our internal users and customers face. You leverage direct user discovery and can run data analyses yourself to ground problem framing in real user and business impact.

• AI-fluent. Youve used AI tools - whether for data analysis, prototyping, or documentation - and you have a point of view on where they help in a domain like this.

• Effective in cross-functional teams. You work well with a wide variety of people and are eager to be on a team where Product, Engineering, and Data Operations stakeholders collaborate daily. 

• Experience leading and managing senior cross functional stakeholders. You bring others along by articulating the “why” behind decisions, translate technical concepts for non-technical stakeholders, and treat enablement as a core part of the job. 

• Organized and dependable. You follow through on commitments, flag risks and questions early, and deliver reliably even under real operational pressure (e.g. Back to School season). 

• Strong learner. You actively learn from experience, solicit and apply feedback quickly, and can articulate how your thinking changed as a result.

Nice to Haves

• Experience in education, working with multilingual learner communities, or a meaningful connection to the mission.

• Capable of querying data (SQL or similar) to investigate a problem or support a decision — ideally with some comfort in a cloud data warehouse like Snowflake.

• Basic data modeling familiarity — schemas, relationships between datasets, identifiers, and downstream data dependencies.

• Experience with SIS (student information system) data, interoperability standards (OneRoster or similar), or hands-on experience with rostering platforms like Clever or ClassLink.

• Exposure to internal tooling in enterprise B2B SaaS, where some of your “customers” are internal operations teams in addition to external end users.

• Familiarity with product discovery methods: user interviews, lightweight prototyping, structured experimentation.

Travel Expectations

Travel Expectations

• Boston-area strongly preferred

• Role requires in-person presence in Boston at a minimum of two days each month, plus company offsites