About SignalFire
SignalFire is the first VC firm built like a technology company to better serve the needs of founders as they build and scale their startups. With approximately $3B in assets under management, SignalFire invests in applied AI companies from pre-seed to Series B in key sectors, including healthcare, cybersecurity, infrastructure, consumer, and other enterprise verticals.
The firm’s Beacon AI platform tracks over 650M employees and 80M organizations, giving the firm an unmatched data advantage in identifying and supporting world-class startups. Its sector-focused investors and a dedicated team of seasoned operators drive SignalFire at startup speed. They provide support across a company’s full lifecycle through data and resources tailored by growth stage, plus a diverse ecosystem of partners and customers. Notable investments include Frame.io, Grammarly, Grow Therapy, EvenUp, and Stampli.
Learn more at www.signalfire.com
Role Description
Signalfire is looking for an exceptional engineer who is passionate about building robust data infrastructure that powers complex analytical workflows, machine learning processes, and data-intensive web application. As our data engineer, you will work closely with our investment, portfolio, talent team, and the rest of our engineering organization to build best-in-class tools that help us explore potential investment areas and support our portfolio companies.
What you’ll be doing:
Building industry-standard backend architecture and data pipelines for our AI platform, Beacon which helps our firm invest in the best startups in the market
Procuring and evaluating potential new data sources in service of identifying, diligencing, and supporting startups
Build and maintain scalable, maintainable data transformation pipelines using Python, Spark, dbt, apache/airflow to power the whole company's data science and analytics needs
Stand up new low-latency data processing infrastructure to provide clean data to machine learning models
Improve workflow orchestration and automation processes for existing systems
Your background:
2 to 6 years of experience working as a data engineer
A solid conceptual grasp (and preferably hands-on experience with) orchestration frameworks like Airflow, Dagster, Prefect, or similar
Experience with ETL, data processing, pipelining, and sanitizing
Experience working on complex data pipelines using SQL, Redshift, Python, dbt
Experience building backend infrastructure and architecture required to power frontend features
Understanding of data modeling strategies for both transactional and data warehousing workloads
Exceptional problem solving, analysis, decomposition, and communication skills applied within an agile development environment
BS/MS in statistics, computer science, economics, or a similarly quantitative field
Takes pride working on large projects from scratch to completion
San Francisco Bay Area or New York based
Why SignalFire?
In addition to working directly with our team at the forefront of a hybrid human + technology investment approach, you’ll also work closely with founders to help them solve major problems.
Our culture is one that breeds creativity and impact and puts you in control of your own destiny.
End-to-end ownership: Engineers at SignalFire own the full stack—from data acquisition and model development to infrastructure and product delivery. This extends beyond code; you'll work directly with the investment team, gaining insight into how your work shapes strategic decisions.
Empowered decision-making: We’ve cut the bureaucracy of big companies but kept their resources. Have a strong idea? Pitch it. You’ll get budget and ownership. We move like a startup but execute with the discipline of a mature company.
Versatile technical expertise: We value engineers who blend startup agility with enterprise depth. You'll wear many hats—tuning infrastructure one day, refining algorithms or designing features the next—building a skillset rarely found elsewhere.
Creative autonomy: At SignalFire, creativity isn’t just valued—it’s essential. We tackle problems without clear precedents, where sharp judgment and innovation matter more than technical orthodoxy. Success means balancing analytical rigor with a bias to ship, learn, and iterate.
You can read more about life on the engineering team here: https://www.signalfire.com/blog/engineering-at-the-heart-of-venture-capital
Compensation
USD 170k-270k base salary/year based on experience + Carried Interest
