Senior Data Engineer — Geospatial Pipelines & AI Platform

Superorganism; Seattle (WA); In loco; USD 150.000 - 180.000; Tempo pieno

Descrizione del lavoro

Aarden in Seattle seeks a high-autonomy senior data engineer to own core datasets and the data pipeline that keeps them current. You’ll ensure data quality and reliability across S3, Iceberg, Postgres, and Lambda, while improving observability and performance.

You’ll partner with product and analytics to build datasets for new features, extend pipelines for new sources, and advance geospatial data capabilities with PySpark, Sedona, and related tools. You’ll own the roadmap and ship thoughtfully.

Competenze

• 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.

Mansioni

• Own and operate the data platform including data infrastructure components.
• 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 improve reliability or efficiency.
• Collaborate with product to build datasets for new features.
• Co-develop intelligence products with the analytics team.

Conoscenze

Python

SQL

Data pipelines

Observability

Git workflows

5+ years experience

Formazione

Bachelor's degree

Strumenti

Prefect/Airflow/Dagster

PostgreSQL

PostGIS

PySpark

Apache Sedona

Descrizione del lavoro

Aarden in Seattle seeks a high-autonomy senior data engineer to own core datasets and the data pipeline that keeps them current. You’ll ensure data quality and reliability across S3, Iceberg, Postgres, and Lambda, while improving observability and performance.

You’ll partner with product and analytics to build datasets for new features, extend pipelines for new sources, and advance geospatial data capabilities with PySpark, Sedona, and related tools. You’ll own the roadmap and ship thoughtfully.