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Open nowPosted 56 days agoWe saw it 7 min after it went up

Staff Data Engineer

Atticus16 open roles

Pay
$1,200 a month
Where
Remote
Work mode
Remote
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Your applicationOpen nowStaff Data EngineerAtticus · Remote
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The clock on this job

Early applications get read.

11.5% of postings close within 7 days. Measured by our own scanner across the market. Atticus postings stay open a median of 51 days.

Share of postings closed within
  1. 2.0%1 day
  2. 4.3%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: posted 56 days ago

Atticus median: 51 days open

The posting

ABOUT ATTICUS

At any given time, 16 million Americans are experiencing a crisis that requires urgent help from our legal system or government. The right assistance could transform their lives. But today, most never get it.

Atticus makes it easy for any sick or injured American to get life-changing aid. Our mission is to tear down barriers between people in crisis and the aid they deserve. In the last six years, we’ve become the leading platform connecting people with disabilities to government benefits.

We also help victims of accidents, misconduct, and violence get compensation from insurance. So far, we’ve helped hundreds of thousands of people access over $10 billion in life-changing aid —and earned over 20,000 five-star reviews. And we’re just getting started.

We've raised more than $100 million from top VC firms like Forerunner, Google Ventures, and True Ventures, and we’re on our way to creating a category defining business assisting Americans in need.

THE JOB

We are looking for our first in-house Data Engineer to own and evolve our core data infrastructure. This is an early and high-impact role. As the data engineering function grows under Engineering, you'll have a real voice in shaping how it's built - the processes, standards, and team culture.

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 underrepresented 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 for all employees —and generous benefits:

- Medical and dental insurance with 100% of premiums covered for employees and their families

- 15 vacation days & ~20 paid holidays each year (including two weeks at end-of-year)

- Free membership to OneMedical

- $600/year internet stipend

- $1,000/year 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 $240,000 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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