Movement Labs is an incubator and consulting firm that uses technology, data, and experimentation to stop fascism and build progressive power. We help progressives win and defeat MAGA extremists through year-round work grounded in research and real-world testing. Our team partners with leading advocacy groups, grassroots organizers, and electoral campaigns to develop innovative tactics, win elections, and shift power for the long term.
As the R&D powerhouse for the progressive movement, we’ve run over 100 randomized control trials (RCTs) on voter behavior and helped hundreds of organizations increase their impact. We work hard, and the environment evolves rapidly. We are adaptable, nimble, and shift quickly as needed to meet the moment. We are looking for candidates that thrive in this type of environment.
We are looking for 3 roles, Senior and Mid-level Data Engineers to join the Tech department. You will be a part of an 8-person data engineering team, and will have a lot of ownership and ability to make an impact. You’ll work cross-functionally in a collaborative, startup-like environment.
What the work looks like for our data team:
- Design and implement scalable data architecture for targeting and engagement
- Serve as technical partner to program teams
- Extend our foundational datasets to facilitate new outreach strategies
- Load-test our systems to prepare for elections
- Maintain key datasets for polling images and precinct cross-matching
- Develop standardized experimental frameworks for testing campaign effectiveness
- Build AI tooling that makes our own team faster — QC agents for data deliveries, the evals to trust them, and context systems that keep our repos self-documenting
Our data team’s work mixes greenfield builds, pragmatic plumbing, incident response, and operational work. The relative mix shifts with the political calendar.
This role is fully remote. This position has an initial term of six (6) months beginning on the employee's start date.
Responsibilities
- Shape the pipelines and integrations feeding our RCT platform and our foundational voter datasets: the APIs, replication, federation layers, experiment randomization, and the failure modes that come with running data systems for hundreds of partner organizations on a non-negotiable political calendar
- Extend our data platform and orchestration layer, and optimize it for cost, runtime, and reliability so it holds up during the elections, with millions of outreach attempts
- Lead projects that span multiple systems and teams — scoping, designing, and driving them to real milestones
- Hold the bar on quality — test and validate your own work, review teammates' code, and mentor through that review
- Document and communicate — make your systems understandable to teammates, stakeholders, and non-engineers
- Rotate through on-call and rapid response, including evenings and weekends during high-stakes moments like election cycles
Requirements
- Passionate about progressive politics and leveraging data, technology, organizing and research to build political power
- 3-6+ years of experience (Senior or Mid-level) in designing, building, and operating production data pipelines and integrations
- Strong proficiency in SQL and Python
- Experience building production software across a modern data stack — cloud data warehouses (BigQuery or similar), a transformation framework like dbt, and an orchestrator like Dagster or Airflow
- A track record of leading technical work across multiple systems or teams, and scoping ambiguous problems end-to-end
- Sound judgment about when to refactor, when to ship pragmatically, and how to leave systems better than you found them
- Strong written communication — you document what you build and can explain complex systems to non-engineers
- Genuine commitment to the mission of stopping fascism and building progressive power, and comfort operating on a political calendar
Nice to Have:
- Experience in the progressive, political, advocacy, or nonprofit sector — including awareness of c3/c4/PAC boundaries and the sensitivities of political and voter data
- Familiarity with election results, voter file data, and the tools campaigns use to organize, text, and contact voters
- Experience on Google Cloud Platform
- Experience in on-call rotations and mentoring less-experienced engineers
We’re looking for candidates with a wide range of skills and experience. If you’re excited about the job, even if you don’t match all the characteristics, we encourage you to apply.
Benefits
- Base salary of $90,000-$119,000, plus a $5000 end of cycle bonus and a work life stipend of $2100 in pre-tax dollars to support employees during our highest-intensity work period.
- Excellent health, dental, and vision benefits, 401(k) matching, and unlimited Paid Time Off (vacation time is limited during election sprint, August 24-November 3).
- Remote first culture with teammates all around the country.
- This position has an initial term of six (6) months beginning on the employee's start date. We love to keep top performers if possible.
Applications submitted by July 31, 2026 will be given priority. Applications may be reviewed earlier on a rolling basis so it benefits candidates to apply as soon as possible. The application process includes a phone screen, an exercise, and a full interview with the hiring manager. Due to the nature of our work, the process is moving quickly, and we hope candidates will start as soon as possible. Applicants must be legally eligible to work in the United States. We are not able to provide sponsorship at this time.
Movement Labs is an equal opportunity employer with a commitment to economic and social justice. Women, people of color, LGBTQ people, people with disabilities, and members of other historically disenfranchised populations are strongly encouraged to apply. If you require accommodations as part of the hiring process, please contact careers@movementlabs.com.
Applications are reviewed by our hiring team—not automated systems. Our hiring process may include AI-assisted analysis of candidate materials, however, hiring decisions are made by human reviewers.
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