Senior Data Engineer

Why Join AngelList 

We’re solving some of the hardest problems in venture capital and private markets. You’ll work with a team that values precision, urgency, and long-term thinking. If you want to shape how startups are funded and built, this is the place.

About AngelList

We exist to accelerate innovation by increasing the number of successful startups in the world. We do this by building the financial infrastructure that makes it easier for more people to invest in world-changing companies.

AngelList is the nexus of venture capital and the startup community. We support $171B+ in assets and have powered investments into over 13,000 startups—over 300 of which are unicorns. Today, 57% of top-tier U.S. VC deals involve investors on AngelList. While our scale is large, our ambition is larger.

If you're excited to build the future of private markets, come build with us.

About the Role:

We’re building a data platform that helps AngelList make better decisions faster and turn data into a lasting company advantage.

Data sits at the center of how we understand our marketplace, guide product decisions, and support investors and founders across the AngelList ecosystem. Our goal is to create a platform where data is reliable, well-governed, and easy to build upon so teams can move quickly with confidence in the metrics they rely on.

This role is key to realizing that vision. You’ll shape how data flows through the company, from ingestion and orchestration to modeling, analysis, and the systems that keep metrics consistent and trustworthy over time. You’ll also help define the long-term architecture and standards of our evolving data platform.

We are a small, high-leverage team with strong ownership. AI is part of how we work, helping accelerate development, improve documentation, and reduce manual overhead so we can focus on higher-impact problems. If you enjoy building durable systems and raising the structural bar of a data platform, this role offers the opportunity to do exactly that.

Responsibilities

• Standardize ingestion patterns and orchestration across our data stack to improve reliability and reduce operational drift
• Establish durable modeling patterns and canonical metric definitions so teams can rely on consistent sources of truth
• Translate business and product questions into well-structured datasets, models, and analyses that support better decision-making across the company
• Build and evolve monitoring and alerting that improves observability across our data pipelines and platform
• Partner with engineering teams to introduce data contracts and clearer ownership of upstream schemas
• Continuously improve the performance, maintainability, and cost efficiency of our data platform

What We Are Looking For

• You have 5+ years of experience designing and evolving production data platforms and understand the tradeoffs between speed, reliability, and long-term maintainability
• You have strong SQL skills, production-level Python proficiency, and hands-on experience with modern data platforms such as Snowflake, Airflow, and dbt, ideally in an AWS environment
• You operate end to end across the data stack and bring high ownership and agency, moving easily between pipelines, modeling, analysis, and stakeholder conversations
• You have built or maintained canonical data models and metric definitions that serve as sources of truth across teams
• You partner effectively with engineering, product, and business stakeholders to translate real-world questions into well-structured datasets, models, and insights
• You actively leverage AI in your daily work, e.g., to prototype transformations, generate or review code, automate recurring workflows, or make common data requests self-serve

Working Here

If you don’t meet every requirement above, we still encourage you to apply. We value complementary strengths and operators who learn by doing.

AngelList has offices in a few cities, with our engineering hub in San Francisco. We’re building our engineering and product teams around this hub to make the most of in-person collaboration. We have a hybrid in-office model: teammates come in at least 2 days per week (Tuesdays and either Wednesday or Thursday).

Compensation:
The compensation for this role consists of a competitive base salary, benefits, and equity package. The base salary for this role is $190,000+ annually but actual will vary based on a number of factors including a candidate’s professional background, experience, and location. Additional details about our Total Rewards package will be provided during the recruitment process.