Cyvl is building an Infrastructure Intelligence Platform that turns real-world sensor inputs into trusted, client-ready geospatial deliverables. In this Data Engineer role, you’ll design and scale the pipelines and data platform that move raw LiDAR, imagery, and GPS data through processing, quality assurance, and onward use by product, AI, and analytics teams. The work is focused on production reliability, automated data quality, and AWS cost and performance improvements.
What you’ll do
- Design, build, and operate pipelines that take sensor data from ingest through to client-ready geospatial outputs.
- Build and maintain a data platform so product, AI, and analytics teams can find and use data quickly.
- Create automated data quality checks and monitoring to detect issues before customers encounter them.
- Collaborate with Data Operations and GIS teams to automate manual workflows and increase throughput.
- Improve cost and performance of large-scale processing on AWS.
Core requirements
- 3+ years building production data pipelines or data platforms.
- Strong Python and SQL skills.
- Experience with cloud data infrastructure (with AWS preferred) and workflow orchestration using Airflow, Dagster, Prefect, or similar tools.
- Experience making large, messy datasets reliable and consistent.
- Comfort owning systems end to end, from design through on-call.
Tools you may use
- Python, SQL, AWS
- Airflow, Dagster, Prefect
- PostGIS, GDAL, GeoParquet, H3, Iceberg, Delta, DuckDB, Spark
- Docker, Kubernetes, Terraform
Additional role context
Every Cyvl drive captures LiDAR, imagery, and GPS data that must become something city engineers can trust. You’ll build and scale the pipelines and data platform behind the Infrastructure Intelligence Platform, taking data through processing, AI inference, and QA to deliver geospatial outputs that clients can use.
This role is based in Somerville, MA (hybrid), or remote from San Francisco, CA.
Nice to have
- Geospatial experience such as PostGIS, GDAL, GeoParquet, H3, or other spatial indexing.
- Experience with sensor data including LiDAR point clouds, imagery, and GPS/IMU.
- Lakehouse formats and engines like Iceberg, Delta, DuckDB, or Spark.
- Familiarity with Docker, Kubernetes, and Terraform.
- Supporting ML training and inference pipelines.
Compensation & benefits
Compensation range: $125,000 - $195,000 per year.
- Equity
- Health, dental, and vision (Cyvl covers most premium for you and your family)
- 401k with a real match, vested day one
- Generous PTO and Paid Parental leave
- Learning stipend
- Paid to live close (monthly bonus for living near the Boston office)
- Team events
Values
- Real: Authentic and transparent, solving real problems with simple, effective solutions.
- All Out: Bold, driven, and committed to results that matter.
- Accelerating: Always learning, growing, and moving with intention.
- Reliable: Following through and delivering at a consistently high bar.
- Empowering: Lifting each other up and helping governments build infrastructure they can be proud of.
