The Global Partnerships Data Engineer will own and advance critical data infrastructure, systems, and automation that support global partnerships work at Andreessen Horowitz (a16z). The role operates independently, leads cross-functional initiatives, and turns ambiguous business needs into scalable systems, reliable pipelines, and actionable insights.
Role Overview
The Global Partnerships Data Engineer is responsible for core datasets, data pipelines, and automation that enable global partnerships activities at a16z. You will act as a technical and strategic thought partner to Global Partnerships and adjacent teams, translating data practice requirements into scalable process design and practical insights for LP-facing and internal workflows.
Key Responsibilities
- Own critical systems, including the Global Partnerships core datasets and data pipelines, and advise teams on data practices, automation, and scalable process design
- Design and maintain scalable data infrastructure and reliable pipelines to connect Global Partnerships systems and reduce manual effort and error rates
- Maintain high standards for data accuracy by monitoring for discrepancies across platforms and correcting issues
- Evaluate and implement tools and integrations that improve visibility, connectivity, and decision-making
- Identify, pilot, and scale AI tools and agentic workflows that reduce manual work, then drive adoption through training, documentation, and change management
- Lead automation, process development, and operational scaling to improve data accuracy, reliability, and speed
- Serve as an AI thought partner by staying current on emerging tools and translating them into high-leverage improvements to LP-facing and internal processes
- Build visualizations and quantitative analyses for fund and investment performance, including projected exit scenarios and liquidity and follow-on decisions
- Develop strong fluency with the firm’s portfolio company information database and manipulate/analyze its data to produce insights
- Refine and calibrate portfolio performance analyses to ensure they remain current and relevant
Required Qualifications
- Minimum of 5 years of experience; data analytics or data engineering experience is preferable
- Bachelor’s degree in Computer Science, Data Science, Economics, Finance, Accounting, or a technical field preferred (not required)
- Critical attention to detail for written materials, charts, tables, and spreadsheets, with the ability to track changing data and facts across multiple documents
- Strong writing skills and the ability to communicate effectively in written form
- Demonstrated experience building and maintaining data workflows, automations, or integrations using Python, Javascript, or a comparable programming language
- Proven ability to lead ambiguous, cross-functional projects with substantial autonomy and influence across technical and business teams
- Experience owning or administering complex data pipelines or other critical business systems, emphasizing data completeness, governance, and integration
- Low ego, high empathy, and the ability to collaborate effectively with diverse teams
Technologies
Compensation
The anticipated salary range is USD 269,000 - 314,000 per year. Actual starting pay may vary based on factors including experience, skills, and scope.
Benefits
- Eligible to participate in the a16z carry program
- Eligible to participate in various discretionary bonus programs
- Health
- Dental
- Vision
- Disability
- Life insurance
- 401K plan
- Vacation
- Sick leave
Location and Work Style
This role is based in Menlo Park, CA and is listed as onsite. Candidates open to the San Francisco Bay Area are considered.
Additional Expectations
- Own and advance the Global Partnerships data ecosystem
- Champion AI adoption across Global Partnerships
- Use data to enable practical insights on portfolio and industry
Culture and Team Values
- Commit to first-class business and execution
- Take a long view of relationships
- Bet on the future
- Recognize differences and win as a team
- Celebrate the good times and do it for the team
- Play to win
