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Treeswift

Provides tree-level forest inventories via drones

Data Platform Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeNew York, NY, USA

About the Job

Requirements

  • Bachelor’s degree in Computer Science, Computer Engineering, Math, or a related field, or equivalent experience.
  • At least 4 years of data engineering or backend engineering experience focused on pipelines, orchestration, or platform.
  • Hands-on experience building and maintaining production data pipelines using Airflow, Prefect, Luigi, or similar tools.
  • Cloud experience with object storage and data at scale is required; prior AWS experience is not required.
  • Practical familiarity with Kubernetes and container-based deployments, including running workloads on Kubernetes, configuring resources and volumes, and debugging pod or worker issues.
  • Ability to own work end-to-end by designing, implementing, testing, and operating pipelines and related tooling, and to learn new parts of the technology stack as needed.
  • Ability to collaborate and communicate effectively with machine learning, hardware, and product stakeholders and explain tradeoffs clearly.

Responsibilities

  • Design, build, and maintain large-scale data pipelines that process diverse physical data, including imagery, audio, and point clouds.
  • Develop and evolve Airflow DAGs that orchestrate complex, multi-step workflows, including tasks that fan out and in, Python and Kubernetes operators across generalized and specialized node pools, and dynamic DAG generation.
  • Work with the in-house machine learning team on feature pipelines and model deployment within DAGs, and coordinate with the hardware team on ingestion and data formats.
  • Improve DAG design and execution, resource and cost tuning, reliability, and observability.
  • Contribute to running Airflow and Kubernetes in the cloud.
  • Work with machine learning, hardware, and software engineers to turn technically complex requirements into high-fidelity datasets that customers can use to make informed decisions.
  • Partner with large utilities and contribute to developing workflows for work planning, construction, and disaster response.

Desired Qualifications

  • Experience in early-stage or fast-moving environments where scope and ownership evolve.
  • Experience with Apache Airflow, especially version 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.

About the Company

Treeswift

Provides tree-level forest inventories via drones

Treeswift collects and sells precise forest data. It uses sensor suites attached to drones and backpacks to gather tree-level measurements (diameter, height, quality, merchantable products, species, stem defects) and geospatial information across large areas, focusing on carbon and timber inventories for forest management. The data is processed with advanced algorithms to create detailed inventories for each tree. This product is sold as an operational database of carbon and timber metrics that foresters can use to make decisions. Unlike broader, less granular methods, Treeswift delivers verifiable, per-tree data collected in real time over large landscapes, with the involvement of foresters in its development. The company’s goal is to provide accurate, scalable, and reliable forest inventories that improve decision-making in forest management and carbon/timber accounting.

Company size
51-200
Company stage
Early VC
Total funding
$15.6M
Headquarters
New York City, New York
Founded
2020

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