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Lead Data Engineer
- New York, New York, United States
- New York, New York, United States
Über
You’ll sit at the intersection of our Engineering and Business Operations teams, which means you’ll spend your time both building reliable, scalable systems and translating business needs into well-designed data products. You’ll work closely with data scientists, business analysts, and product leaders to make sure our data is clean, accessible, and trustworthy.
What You’ll Do
Own and operate our data warehouse, pipelines, and transformation layer
Design, build, and maintain scalable, reliable data pipelines that ingest data from across our platform and third‑party sources, ensuring data is always available and trustworthy for downstream consumers
Partner with data scientists and analysts to deliver clean, well‑documented datasets and optimize query performance so teams spend less time wrangling data and more time generating insights
Incrementally improve and modernize our existing data systems – you won’t build everything from scratch, but you’ll know how to assess what we have, prioritize what matters, and migrate thoughtfully
Implement data quality monitoring, alerting, and documentation practices that build trust across the organization
The role is a rare opportunity to join a fast‑growing Series C startup that doubles as a B‑corp social enterprise. Every project you take on will help clients in need get the help they deserve, and you’ll shape our company culture as we scale. We’re looking for data scientists who are excited about our mission and the challenges it entails.
Qualifications Required:
4+ years of professional experience in data engineering, ideally at a high‑growth startup or fast‑moving team within a larger organization
Hands‑on experience with the modern data stack – proficiency with BigQuery (or a comparable cloud warehouse), dbt, and an orchestration tool like Dagster or Airflow
Strong SQL skills and fluency in Golang, Python, or another common Data Engineering language
Track record of improving or modernizing data systems iteratively – you’re comfortable inheriting legacy infrastructure and systems and making them progressively better
Strong communication and collaboration skills – able to work fluidly across both technical and business‑oriented teams
Bonus / Nice‑to‑Have:
Experience transitioning data infrastructure from an outsourced or contractor model to an in‑house team
Familiarity with data observability tools
Experience supporting or collaborating with a data science function, including ML feature pipelines
We are strongly committed to building a diverse team. If you’re from a background that’s under‑represented in tech, we’d love to meet you.
Salary and Benefits This is a rare opportunity to join a startup that has strong traction (substantial funding, well‑respected backers, tremendous growth, and many happy customers) but is still small enough that you can have a huge impact and play a role in shaping our culture.
We’re a certified B Corporation tackling a critical social problem. Our mission to help people in need drives everything we do, and your work here will touch many lives.
We offer competitive pay—including equity—and generous benefits:
Medical and dental insurance with 100% of employee premiums covered
15 vacation days & ~20 paid holidays each year (including two weeks at end‑of‑year)
Free membership to OneMedical
$600/year reimbursable stipend for internet service
$1,000 reimbursable stipend for education and training outside of work
Up to $1,200/year student loan repayment assistance
401(k) and optional HSA/FSA
We anticipate the base salary band for this role will be between $174,000 and $230,000 in addition to equity and benefits. The salary at offer will be determined by a number of factors such as candidate’s experience, knowledge, skills and abilities, as well as internal equity among our team.
Location This job is fully remote and we’re committed to empowering everyone with flexibility. Work remotely, and travel to LA (on the company dime) as needed to be with your colleagues – usually quarterly, plus offsites. We care a lot about building a great culture and we think some interactions need to happen in person, so we put a lot of thought into retreats, offsites, and other ways to gather.
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Sprachkenntnisse
- English
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