Partner 22, Fund Strategy Engineering & Data at a16z

San Francisco, California, United States -

Full Time

Start Date

Immediate

Expiry Date

15 May, 26

Salary

320000.0

Posted On

14 Feb, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Databricks, SQL, Software Engineering, Data Systems, Applied Analytics, Fund Mechanics, Investment Strategy, Data Pipelines, Machine Learning, Statistical Inference, Predictive Modeling, Econometrics, Natural Language Processing, Quantitative Modeling, dbt, Python

Industry

Venture Capital and Private Equity Principals

Description

Founded in Silicon Valley in 2009 by Marc Andreessen and Ben Horowitz, Andreessen Horowitz (aka a16z) is a venture capital firm that backs bold entrepreneurs building the future through technology. We are stage agnostic. We invest in seed to venture to growth-stage technology companies, across AI, bio + healthcare, consumer, crypto, enterprise, fintech, games, and companies building toward American dynamism. a16z has $90B under management across multiple funds. We’ve established a team that is defined by respect for the entrepreneur and the company-building process; we know what it’s like to be in the founder’s shoes. We’ve invested in companies like Anduril, Airbnb, Coinbase, Cursor, Databricks, Deel, Figma, GitHub, Roblox, SpaceX, and Stripe. Our team is at the forefront of new technology, helping founders and their companies impact and change the world. The Role The Fund Strategy Engineering & Data Partner plays a key role in delivering actionable, data-driven insights across all of a16z. This role will leverage Databricks, SQL, and modern software, data, & ML frameworks to construct enterprise-grade datasets, simulations, and analytical tools. The role involves designing automated data pipelines, cleaning and enriching large structured and unstructured datasets, applying advanced statistical and machine learning methods, and developing programmable analyses that address complex business challenges. This role requires strong technical expertise in software engineering, scalable data systems, and applied analytics, paired with a deep understanding of fund mechanics and investment strategy. The Partner will collaborate with central teams such as the software group, investor relations, finance, compliance, and tax to transform complex financial datasets into predictive, decision-grade intelligence. The Fund Strategy team focuses on four core areas: New Fund Formation Modeling and Strategy – Developing models to forecast fund dynamics Fund Management – Managing deployment pacing, portfolio construction, portfolio strategy, and life-of-fund responsibilities Capital Management – Optimizing capital allocation and financial planning Cash and Stock Distributions – Strategizing on distribution methods to maximize returns This position demands proficiency in both the technical aspects of software and data engineering and the strategic understanding of fund management, providing a bridge between data-driven insights and executive decision-making. Must thrive at the intersection of technical execution and business impact. This role requires an in-office presence 3 days a week in our San Francisco, CA office or Menlo Park, CA office. To join our team, you should be excited to: Architect and build automated systems, internal tools, and web applications that collect, classify, and analyze financial data across structured and unstructured sources. Work will be done in partnership with the firm’s software group Own the end-to-end analytics lifecycle—from exploratory data analysis and hypothesis generation to model development, validation, and deployment Guide the technical direction of data and AI initiatives, including architecture, roadmap priorities, and tool selection—applying first-principles thinking to fund analytics Lead development of analytical and predictive systems for investment tracking, portfolio optimization, and fund-level strategy Design and scale modern data pipelines and ML workflows using Fivetran, dbt, Databricks, and Hex—ensuring performant integration of financial data across cloud systems Translate complex datasets into decision-grade insights by applying statistical inference, predictive modeling, and causal analysis for fund pacing, reserve management, and risk assessment Deliver real-time intelligence via dashboards, APIs, and simulations—enabling faster, more consistent decision-making across investment and operating teams Support pro-rata and follow-on investment analysis with scenario modeling and optimization frameworks Conduct public markets analytics using econometrics, natural language processing, and quantitative modeling to inform distribution and exit strategies Build and maintain positive relationships and act as a trusted technical and engineering partner with key groups of the firm including the investment, legal, capital network, and finance teams Own the design and delivery of scalable, executive-facing dashboards that integrate data from finance, ops, and engineering to surface insights on fund performance and investment outcomes for senior stakeholders Support ad-hoc projects related to the Firm’s priorities and initiatives Minimum Qualifications Mastery of modern data and software engineering tools and languages, including SQL, Databricks, dbt, Delta Lake, Python, and orchestration or web frameworks 7+ years of experience building scalable, data-driven software systems or internal tools that support financial decision-making, asset management, or portfolio strategy Degree in Computer Science, Engineering, Data Science, Applied Math/Stats, Finance or similar Deep domain fluency in venture economics, fund modeling, tokenomics, pro rata mechanics, and carry waterfalls Proven experience delivering analytical platforms and predictive models that inform executive decision-making Strong collaborative skills and the ability to work cross-functionally across the various operational groups within a16z Experience leading projects with company-wide impact Experience in mentoring/influencing senior engineers across organizations Proven track record of planning multi-year roadmaps in which short-term projects ladder up to a long-term vision Experience in driving large cross-functional/industry-wide engineering efforts Experience building internal platforms, APIs, or user-facing tools is a plus Candidate must be authorized to work in and be living in the United States Low ego, high empathy, and the capacity to collaborate effectively with diverse teams The anticipated salary range for this role is between $275,000 - $320,000, actual starting pay may vary based on a range of factors which can include experience, skills, and scope. This role is eligible to participate in the a16z carry program and various discretionary bonus programs as well as benefit and perquisite plans including health, dental, vision, disability, life insurance, 401K plan, vacation, and sick leave. a16z culture We do only first class business and only in a first class way We take a long view of relationships, because we are in the relationship business We believe in the future and bet the firm that way We are all different, we recognize that, and we win We celebrate the good times We do it for the team We play to win At a16z we are always looking to hire the absolute best talent and recognize that diversity in our experiences and backgrounds is what makes us stronger. We hire candidates of any race, color, ancestry, religion, sex, national origin, sexual orientation, gender identity, age, marital or family status, disability, Veteran status, and any other status. These differences are what enables us to work towards the future we envision for ourselves, our portfolio companies, and the World. Our organization participates in E-Verify. Click here to learn about E-Verify. Andreessen Horowitz hereby reserves the right to make use of any unsolicited resumes received from outside recruiting agencies and / or individual recruiters without being responsible for payment of any fees asserted from the use of unsolicited resumes.

Responsibilities

This role involves leveraging modern data and ML frameworks to construct enterprise-grade datasets, simulations, and analytical tools to deliver actionable, data-driven insights across the firm. Key duties include designing automated data pipelines, applying advanced statistical methods, and developing programmable analyses to address complex business challenges related to fund strategy.