Vice President, Data Engineering

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.

HarbourVest’s Quantitative Investment Science (QIS) group is seeking a Vice President of Data Engineering to lead the strategy, execution, and scaled delivery of our private equity data platform.

This is a senior technical leadership role responsible for owning platform outcomes end-to-end—architecture, delivery, reliability, and adoption—while directly influencing how data enables investment decision-making across the firm. The VP will combine deep hands-on technical expertise with the ability to mentor senior engineers, scale teams, and deliver complex, high-impact systems in production.

Unlike pure management roles, this position requires active technical engagement in architecture, design decisions, and critical problem-solving, while building a team and operating model that delivers consistently at scale.

The ideal candidate is someone who is:

• A senior technical leader who can operate strategically while staying hands-on in architecture, design, and critical problem-solving.

• Accountable for end-to-end platform outcomes across architecture, delivery, reliability, adoption, and operational excellence.

• Comfortable leading high-impact data engineering work that supports investment decision-making across the firm.

• A strong mentor and team builder who raises the technical bar, develops senior engineers, and scales teams effectively.

• Pragmatic in balancing speed, durability, governance, and production-quality expectations in complex data environments.

What you will do:

• Own and evolve a production-grade, cloud-based data platform supporting deal sourcing, diligence, portfolio monitoring, reporting, and analytics.

• Lead architecture and design decisions across modern data stacks, including Snowflake, DBT, orchestration tools, Azure, and related cloud-native capabilities.

• Ensure data engineering capabilities are tightly integrated with application data needs, including trusted data supply, clear data contracts, reliable pipelines, and production-ready consumption patterns.

• Ensure data quality, integrity, lineage, observability, SLAs, scalability, reliability, and performance across critical datasets and pipelines.

• Build, lead, mentor, and scale a high-performing data engineering organization with strong ownership, accountability, and continuous improvement.

• Drive multi-functional delivery with investment, finance, and operational partners, translating business needs into trusted, usable data products.

What you bring:

• Deep experience designing, building, and operating modern, cloud data platforms at scale, including batch and near real-time data processing.

• Strong proficiency with SQL, Python, Snowflake or equivalent cloud warehouses, DBT, pipeline orchestration tools such as Dagster or Airflow, and Azure data tooling.

• Expertise in data modeling, ETL/ELT frameworks, data quality, testing, observability, performance tuning, and cost optimization.

• Proven track record leading data engineering teams, mentoring senior engineers, and delivering data-centric platforms end-to-end in production.

Education Preferred

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

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

Experience

• 10+ Years of Data Engineering and software delivery experience preferred

• 5+ Years of Technical Project Leadership experience, partnering directly with product, application, and operations teams

#LI-Hybrid

Base Salary Range
$245,000.00 - $260,000.00

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, total compensation may include eligibility for long-term reward programs and a comprehensive total rewards package that may include retirement, health, insurance, paid time off, and wellness 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.