Senior Geospatial Data Engineer

Location: Remote, USA

Company: Atomic Maps

The Role

The Senior Data Engineer leads backend development for Atomic Flow, Atomic's cloud-native geospatial data management platform, and the APIs built on it. The scope spans orchestrated, containerized ETL pipelines that enrich imagery, LiDAR, video and telemetry, along with the medallion data framework, Atomic APIs and internal Python SDK. This work links GIS assets to imagery and annotations, enabling customers to scale asset inspection and management.

The role is hands-on across video, ortho, drone and mobile imagery, point clouds and mesh, and develops new capabilities that support ML and an asset-centric data model. The Senior Data Engineer shapes technical direction and scalability for the platform, works independently, and balances cost, scale and customer impact in technical decisions.

The Senior Data Engineer partners closely with Product and Delivery, applies AI to engineering problems, embraces innovation, and draws on deep experience to evaluate new tools and approaches.


CORE RESPONSIBILITIES

Asset-Centric Search and Data Model

  • Lead and expand asset-centric search across the platform

  • Design and maintain the database layer connecting GIS assets, ML annotations and source data

  • Develop new capabilities supporting ML workflows and an asset-centric data model

Data Pipeline Engineering

  • Build and operate pipelines that ingest imagery, point clouds, video and telemetry at scale

  • Convert source data to cloud-native formats, including COG, COPC and GeoParquet

  • Enrich catalog metadata with spatial, temporal, sensor and asset context

Medallion Data Framework

  • Manage the bronze, silver and gold data layers across the platform

  • Define data contracts, schema evolution, quality checks and lineage

  • Keep each layer reliable, auditable and analytics-ready

Orchestration and Containerization

  • Work with the engineering team to build and maintain orchestrated workflows for ingestion, post-processing and ML jobs, including scheduling, retries and monitoring

  • Make long-running jobs observable and recoverable

  • Containerize pipeline and service workloads for consistent deployment across AWS and Azure

  • Partner with DevOps on builds, deployments and resource efficiency

APIs, SDK and Integrations

  • Serve as primary developer of our internal APIs, which delivers thumbnails, tiles and streaming content to Atomic Maps’ product, GIS clients and customer systems

  • Build platform APIs for search, discovery and data lineage

  • Drive API performance, reliability and roadmap as data volumes grow

  • Build and maintain the internal Python SDK with the engineering team, including releases, versioning, documentation and testing

  • Keep the SDK aligned with platform changes for internal teams and customers

  • Develop integrations with the GIS, ML and design ecosystems

Engineering Standards and Collaboration

  • Collaborate with the team’s lead architect on technical standards and system design

  • Write clear technical documentation and conduct code reviews for high-quality, testable code

  • Work across Delivery, Product, DevOps and Data Engineering teams

  • Commit to delivery dates, track work transparently and raise risks early

AI-Enabled Development

  • Use AI agents to write and test code, applying context engineering for effective agentic workflows

  • Integrate AI tools across development, testing, documentation and data operations

  • Identify opportunities to build AI capability into pipelines and catalog enrichment


QUALIFICATIONS

Required

  • 8+ years of data engineering experience, including 3 to 5 years owning production pipelines end to end

  • Strong Python skills, including building and maintaining a library or SDK used by other teams

  • Hands-on experience with workflow orchestration tools such as Airflow, Argo, Prefect or Dagster

  • Track record designing medallion or layered data architectures with Parquet, Iceberg, Delta or comparable formats

  • Experience building and operating FastAPI services that serve large binary or tiled content

  • Production use of Docker and Kubernetes on AWS or Azure

  • Experience managing object storage at scale (hundreds of terabytes or more)

  • Proven ability to work independently and drive technical direction without close oversight

  • Strong fluency with AI tools and a record of using them to increase engineering output without sacrificing quality

Preferred

  • Experience with geospatial data and tooling, including STAC, COG, COPC, GeoParquet, GDAL, rasterio or PDAL

  • Experience processing imagery, LiDAR or point cloud data

  • Experience with search and indexing using OpenSearch or Elasticsearch

  • Industry experience in infrastructure, energy, transportation or other asset-intensive sectors

  • Experience with ML pipelines or serving model outputs as structured data

  • Contributions to public open source projects, particularly in geospatial or data engineering

Atomic Maps is an equal opportunity employer. We welcome applicants of all backgrounds and do not discriminate on the basis of any protected characteristic.


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