Vice President, Data Engineering

HarbourVest Partners•Boston, MA

2d•Hybrid

About The Position

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.

Requirements

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.
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

Nice To Haves

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

Responsibilities

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.