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Aarden is seeking a senior data engineer to own and evolve our core datasets and the data pipeline that keeps them current. You’ll ensure data quality, reliability, and have a direct impact on our user-facing products.
You’ll work with Python/SQL and modern lakehouse tech on AWS, maintaining pipelines with Prefect, Airflow, and Dagster. Collaborate across product and analytics to scale the platform from Seattle.
Aarden is a land intelligence platform that helps landowners, investors, and developers figure out what a piece of land can actually be used for, and how to market it.
We've built out a suite of data products to support that goal - pipelines, databases, and AI/ML models that power our maps and AI agents. We have strong product-market fit, and we're now focused on hardening and scaling our data systems. That's where you come in.
We're looking for a high-autonomy senior data engineer to own and evolve two types of assets central to Aarden's future: our core datasets and the pipeline that keeps them current. The datasets bring together property data, geospatial data, and AI-derived intelligence to power our insights and products. The pipeline makes it efficient and reliable to refresh, expand, and improve those datasets as our business grows. You'll be responsible for the quality of the data and the systems behind it, with opportunities to contribute directly to our user-facing product.
Own and operate the data platform
Own the day-to-day reliability and operation of our data infrastructure, including S3, Iceberg, Postgres, Lambda, PMTiles, and raster datasets.
Monitor, troubleshoot, and improve pipeline performance, observability, and data quality.
Extend existing pipelines to support new data sources and transformations.
Use automation and AI-assisted workflows where they make operations more reliable or efficient.
Partner across the team
Work with product to build datasets that support new features.
Co-develop intelligence products with the analytics team.
Keep pipeline and dataset documentation useful and current.
Evolve the platform thoughtfully
Stay current on data and geospatial technologies relevant to our stack. Identify opportunities to improve it, run focused experiments, and recommend changes when the benefits justify the tradeoffs.
Must-have
Owned the operation of one or more production data pipelines for a continuous period of at least 12 months
Experience with relational databases and lakehouse architectures
Strong Python skills; Experience with workflow orchestration (Prefect, Airflow, Dagster, or similar)
Curiosity and excitement about AI and the impact it can have on our ways of working as developers
Comfort working in a git-based, CI-friendly workflow
Minimum of 5 years of professional experience
Strongly preferred
Experience with geospatial data and associated tooling (GDAL, GeoParquet, PostGIS, Apache Sedona, or similar)
Experience working in full-stack environments, where your work can directly impact the application layer
Comfortable with PySpark or similar distributed data processing
Experience with Apache Sedona or other cloud spatial-compute platforms
Experience building observability/logging layers for data pipelines (not just app services)
Experience with socioeconomic, property, parcel, real estate, or land data
Nice To have
Experience using AI agents to improve data architecture in a real production codebase
Experience in real estate/land, energy, forestry, or agriculture tech
Experience in data scraping; ideally via agents.
Languages: Python and SQL. TypeScript/Node is a plus for our Application layer and AWS ingest paths.
Orchestration & compute
Prefect 3 for pipeline orchestration (YAML/config-driven flows, retries, logging)
Coiled for elastic EC2 workers on GDAL-heavy and batch Python jobs
Wherobots (managed Apache Sedona / PySpark) for large-scale spatial joins, parcel ingest, and lakehouse work
Data lake & formats: Apache Iceberg, Cloud-Optimized GeoTIFF (COG), and PMTiles. Queried with PySpark and DuckDB.
Geospatial: GDAL, rasterio, GeoPandas, and tippecanoe. Large-scale spatial work runs on Sedona/Spark via Wherobots.
Databases & serving: PostgreSQL + PostGIS (and pgvector on the app side) as the production store.
Aarden is a high-trust, high-output team. We're striving to be intentional about our team growth. This allows us to test the outer boundaries of our individual capabilities, while also going deeper on developer tooling and support. You'll work hard here, and we've got your back.
Practically, this means you'll be asked to take on large projects, have a high bar of expectations to meet, and have a strong support system to help you meet that high bar. That support system includes:
At least 2 in-person days per week at our office in Capitol Hill | We've found that while heads-down time at home is fantastic for task-related productivity, in-person time is magic for longer-form productivity. Our in-person days are used to plan, troubleshoot, and check-in with each other on progress and questions. Expect team lunches and whiteboarding.
Focused ownership in your role | The rest of the team is here to help you and cares about the evolution of our data products. With that said, we'll be looking to you to own your lane, go deep, and own the development of these products.
Dedicated monthly AI tooling budget | We're in a golden era of AI-powered developer tooling. We strongly encourage augmenting your output with AI tools, and have a dedicated & flexible budget for every team member to support that setup. We care about what you ship, not how.
Reports to: CTO
Compensation: $150,000 - $180,000 based on skills and experience
Location / remote policy: Seattle-based, able to commute to our office in Capitol Hill