Data Platform Engineer
About The Position
Treeswift empowers energy companies to modernize their field work to meet the growth and challenges ahead by building physical AI for the field worker. Their technology, powered by cutting-edge hardware, sensors (LiDAR, camera, etc.), AI, and software, revolutionizes work in tough environments. Since their first pilot in June 2024, they have rapidly grown, working with major US utilities to reduce wildfire risk, avoid construction delays, and accelerate storm recovery. The team comprises experts in robotics and enterprise software development, with funding from leading investors. They are headquartered in midtown Manhattan with offices in San Francisco and Philadelphia, and are seeking ambitious individuals to build the future of field work.
Requirements
- Bachelor’s degree in Computer Science, Computer Engineering, Math, or a related field (or equivalent experience).
- 4+ years of data engineering or backend engineering experience with a focus on pipelines, orchestration, or platform.
- Hands-on experience building and maintaining production data pipelines (e.g. Airflow, Prefect, Luigi, or similar).
- Experience with cloud object storage and data-at-scale (AWS and S3 experience preferred).
- Comfort with Kubernetes and container-based deployments in practice: running workloads on K8s, resource and volume configuration, and debugging pod/worker issues.
- Ability to own work end-to-end: design, implement, test, and operate pipelines and related tooling.
- Strong collaboration and communication skills; ability to work well with ML, hardware, and product stakeholders and explain tradeoffs clearly.
Nice To Haves
- Experience in early-stage or fast-moving environments where scope and ownership evolve.
- Experience with Apache Airflow (especially 3.x) and/or Astronomer.
- Experience with geospatial data, imagery, lidar, or point clouds.
- Interest in utilities, forestry, or field operations and how data pipelines support those domains.
Responsibilities
- Design, build, and maintain data pipelines at scale, processing terabytes of real-world physical data across various file types (imagery, audio, point clouds, etc.).
- Develop and evolve DAGs to orchestrate complex, multi-step workflows, including dozens of tasks, fan out/in pipelines, and dynamic DAG generation.
- Work closely with the in-house ML team on feature pipelines and model deployment within DAGs.
- Coordinate with the hardware team on data ingestion and formats.
- Scale and harden the data platform, improving DAG design and execution, resource and cost tuning, reliability, and observability.
- Contribute to the management of Airflow and Kubernetes in the cloud.
- Stay curious, collaborative, and cross-functional, working alongside ML, hardware, and software engineers.
- Manage complexity and provide high-fidelity data for customer decision-making.
- Partner with large utilities to develop new workflows in work planning, construction, and disaster response.
Benefits
- Competitive salary and equity package
- Comprehensive medical, dental, and vision coverage for you and your eligible dependents
- Life insurance and short- and long-term disability coverage
- 16 weeks of fully paid parental leave to support all new parents
- Flexible, unlimited paid time off
- 401(k) retirement savings plan
- Free OneMedical membership
- Commuter benefits
- Snacks, goodies, and team lunches provided twice a week
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
Associate degree
