Associate Engineer, Investment Data & Analytics

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.

What you will do

• 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.
• And... Problem solving - perform deep data analysis to support investment model research and identify manual processes worth automating.

What you bring

• 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.
• Experience with DBT and Azure Data Factory and Pipelines; exposure to Snowflake, MS Synapse, or Power BI a plus.
• 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.

Education Preferred

• Bachelor of Science (B.S) or equivalent in Computer Science
• Master of Science (M.S) or equivalent in Computer Science

Experience

• 3-5 Years of Data Engineering or Data Operations experience preferred
• Exposure to private equity or investment management data, partnering with product, application, and operations teams

#LI-Hybrid

Pay and benefits

This USD base salary range represents only one component of total compensation for this role and is provided in accordance with local requirements. This role is eligible for a discretionary annual bonus, which is determined based on individual and overall firm performance. In addition to salary and bonus eligibility, total compensation may include participation in long-term reward programs (typically for more senior-level roles).

We also offer a comprehensive total rewards package that may include retirement contributions, health insurance, income protection, paid time off and leave benefits as well as well-being programs. Our total rewards offerings are influenced by several business factors, and eligibility for certain components will vary by position and geography.

Please note the posted ranges do not apply outside the U.S. and should not be converted to other currencies as a proxy for compensation in other countries.