Data Engineer — Geospatial Pipelines & Infra AI

RiverPark Ventures; San Francisco (CA); Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Equity

Health insurance

401k with company match

Job summary

Cyvl, a Physical AI company, seeks a Data Engineer to build and scale pipelines behind our Infrastructure Intelligence Platform. You will process raw sensor data through processing, AI inference, and QA to provide client‑ready geospatial deliverables. Role can be remote from SF or based in Somerville, MA.

You’ll own the data platform end‑to‑end, collaborating with product, AI, and analytics teams while optimizing costs and performance on AWS.

Qualifications

• 3+ years building production data pipelines or data platforms.
• Strong Python and SQL.
• Experience with cloud data infrastructure (AWS preferred) and workflow orchestration (Airflow, Dagster, Prefect, or similar).
• Experience making large, messy datasets reliable.
• Comfort owning systems end to end, from design through on‑call.

Responsibilities

• Design, build, and operate pipelines that move sensor data from ingest to client‑ready geospatial outputs.
• Build and maintain our data platform so product, AI, and analytics teams can find and use data fast.
• Build automated data quality checks and monitoring that catch problems before customers do.
• Partner with Data Operations and GIS teams to automate manual workflows and increase throughput.
• Improve the cost and performance of processing at scale on AWS.

Skills

Python

SQL

Data pipelines

End-to-end ownership

Problem solving

Tools

AWS

Airflow

Dagster

Prefect

PostGIS

GDAL

GeoParquet

H3

Docker

Kubernetes

Terraform

Job description

Cyvl, a Physical AI company, seeks a Data Engineer to build and scale pipelines behind our Infrastructure Intelligence Platform. You will process raw sensor data through processing, AI inference, and QA to provide client‑ready geospatial deliverables. Role can be remote from SF or based in Somerville, MA.

You’ll own the data platform end‑to‑end, collaborating with product, AI, and analytics teams while optimizing costs and performance on AWS.