Job Description Summary
For over forty years, HarbourVest has been home to a committed team of professionals with an entrepreneurial spirit and a desire to deliver impactful solutions to our clients and investing partners. As our global firm grows, we continue to add individuals who seek a collaborative, open-door culture that values diversity and innovative thinking.
In our collegial environment that’s marked by low turnover and high energy, you’ll be inspired to grow and thrive. Here, you will be encouraged to build on your strengths and acquire new skills and experiences.
We are committed to fostering an environment of inclusion that promotes mutual respect among all employees. Understanding and valuing these differences optimizes the potential of both the individual and the firm.
HarbourVest is an equal opportunity employer.
This position will be a hybrid work arrangement. You will receive 18 remote workdays per quarter to use at your discretion, subject to manager approval. For example, you may choose to work in the office 4 days per week and take one remote day weekly (typically 13 weeks per quarter), leaving 5 additional remote days to be used as needed.
We are building an institutional-grade Client 360 platform to deliver a comprehensive view of our institutional and wealth clients across private markets. This platform will enhance how we report to clients, deliver digital experiences, support fundraising efforts, and provide investment insights. We work closely across Investor Relations, Client Operations, Marketing, Distribution, and Data Engineering to build, deliver, and scale Client 360 — making it a key differentiator in HarbourVest’s growth strategy.
The ideal candidate is someone who is/has:
- Demonstrable ability to transform raw data into trusted, authoritative client-master and activity datasets.
- Sophisticated expertise in SQL for querying, analyzing, and crafting large datasets; proficiency in Python is highly desirable.
- Solid grasp of private markets' investing, including LP/GP structures, fund vehicles, and client reporting needs.
- Experience with agile product management methodologies such as Scrum or Kanban.
What you will do:
- Lead the Client 360 product vision and roadmap, aligning with HarbourVest’s institutional and wealth growth strategy.
- Define and prioritize features and data domains to unify client, investor, and account data across the firm.
- Lead agile delivery, managing product backlogs, release plans, and iterative development cycles.
- Translate business goals into technical requirements, ensuring scalability, data quality, and performance.
- Use SQL and Python to interrogate data sets, validate requirements, and support hands-on backlog refinement.
- Serve as the main liaison between Data Engineering, Product, Platform, and commercial team members.
- Gather and transform client-facing needs into actionable data product specifications.
- Define and lead data models for clients, investors, vehicles, and relationships within the private markets' context.
- Integrate Client 360 with platforms like Salesforce, Kurtosys, DealCloud, and eFront to support reporting and digital experiences.
- Promote cross-functional collaboration and data-driven decision-making, ensuring Client 360 becomes the firm’s single source of truth.
What you bring:
- Demonstrated expertise in coordinating data product ownership, data strategy, or product management in the realms of asset management, private markets, or financial services.
- Strong proficiency in SQL and Python for data validation and prototyping.
- Deep understanding of data governance, MDM, data models, and entity resolution.
- Commercial mindset: Ability to connect data features to client value, distribution growth, and business outcomes.
- Private markets fluency: Understanding of LP/GP structures, fund vehicles, evergreen products, and client reporting requirements.
- Ability to translate business needs into scalable, high-quality technical data product requirements.
- Strong stakeholder communication and cross-functional collaboration skills.
- Skill in agile techniques and leading all aspects of backlogs.
- Critical thinking with a focus on operational excellence and continuous improvement.
Education Preferred
- Bachelor’s degree in Computer Science, Engineering, Finance, or a related field — or equivalent experience.
Experience
- 7–12 years of experience in leading all aspects of data products, developing data strategies, or running products within asset management, private markets, or financial services.
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