We're seeking a senior data engineer to design, build and scale a geospatial data pipeline and data storage, powering hundreds of thousands of wildfire simulations. You will be working with a highly skilled team of various specialties, who will look to you to own the pipeline.

This is a high-impact role—you'll need to move quickly, make pragmatic technical choices and build for scale from day one. You'll be a core technical contributor with ownership over our data flow.

Your work will directly support data-driven wildfire mitigation strategies and help shape how wildfire risk is understood and addressed.

About XyloPlan

XyloPlan helps communities, fire agencies, real estate developers, and insurers reduce wildfire risk through a science-based platform that identifies and mitigates Fire Pathways™, the routes fast-moving fires are most likely to take. Co-founded by fire service professionals and technologists, our work supports smarter resource allocation, improved insurance availability, and greater community resilience across fire-prone landscapes.

Description

Responsibilities:

Design, build, and manage scalable data pipelines, ETL tools
Manage and design databases and data lake/warehouse
Work within a multidisciplinary team to help produce high quality usable data
Ensure accurate data lineage
Develop monitoring solutions to be able to identify and rapidly resolve issues
Create and maintain internal documentation
Write maintainable, well-tested Python and SQL code that other engineers can build on

Qualifications:

7+ years of production data engineering experience with demonstrated scale (TB+ datasets, high-volume batch processing, or equivalent)
Strong track record building complex data pipelines from scratch—you've shipped production systems, not just maintained legacy code
Expert-level Python and SQL for data transformation and pipeline logic
Hands-on experience with distributed batch computing frameworks (Spark, Dask, Ray, or similar)
Production experience with workflow orchestration tools (Airflow, Prefect, Dagster, or similar)
Experience implementing data lake/lakehouse/warehouse patterns
Experience with GCP services (BigQuery, Cloud Storage, Cloud SQL/Postgres, Dataproc, Cloud Run, GKE, or similar)
Strong CI/CD, testing, and version control practices
Excellent communication, collaboration, and teamwork abilities
Excellent problem-solving and analytical skills

Job Type: Full-time

Pay: $140,000.00 - $180,000.00 per year

Benefits: