Associate Engineer, Investment Data & Analytics

HarbourVest Partners•Boston, MA

12d•$145,000 - $175,000•Hybrid

About The Position

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. About Investment Data and Analytics Our organization’s mission is to build technology that lets the firm systematize and scale its understanding of private markets and management of our funds. Our team works side-by-side with investors and quantitative researchers to innovate technology-driven investment processes; solve broad industry problems ranging from AI driven digitization of unstructured data to systematic monitoring of private equity portfolios. The Associate role combines hands-on engineering execution with the opportunity to build deep expertise in private markets data. Working under the guidance of senior engineers, you will develop, test, and operate the pipelines and datasets our investment and research teams rely on — taking on progressively more complex ownership as your technical and domain judgment grows.

Requirements

Demonstrated ability in data engineering and analysis, including data-centric testing and deployment of FinTech applications.
Proficiency in SQL (MSSQL or equivalent RDBMS) and Python, with experience building ETL pipelines for large datasets.
Strong analytical, organizational, and problem-solving skills with outstanding attention to detail, a genuine interest in financial markets, and comfort working in a scrum/agile SDLC environment.

Nice To Haves

Experience with DBT and Azure Data Factory and Pipelines; exposure to Snowflake, MS Synapse, or Power BI a plus.
Exposure to private equity or investment management data, partnering with product, application, and operations teams

Responsibilities

Data engineering — build, test, and deploy pipelines and transformations across financial/economic datasets using modern data stacks.
Infrastructure/platform engineering — run and monitor production data workflows, troubleshoot failures, and implement alerting, logging, and automated testing within CI/CD.
Data Quality — develop validation and reconciliation checks, monitor pipeline health through KPIs, and own root-cause analysis for data issues.
Collaboration — partner with data engineering, DevOps, application, and investment teams to clarify requirements and deliver well-documented solutions.
Problem solving — perform deep data analysis to support investment model research and identify manual processes worth automating.