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AI Civic Data Interoperability Pipeline Developer

Samuel Pham

Full-time · Job · Chicago

About the role

Government data is fragmented by design. A city's permits are in one system, its code violations in another, its property records in a third — all using different identifiers, schemas, and update frequencies. Building useful civic applications requires stitching these sources together, and that stitching is almost always done by underpaid contractors writing one-off ETL scripts that break every time a government system gets upgraded. We build the interoperability layer that makes civic data composable: ingestion adapters for 140 government data portals, an entity resolution system that links records across inconsistent identifier schemes, and a data quality framework that surfaces reliability signals so downstream applications know when to trust a data point. We serve 35 govtech companies and 12 direct government clients. You'll own a portfolio of 20-30 data source integrations: building new adapters as clients request new sources, maintaining existing adapters when upstream formats change, and improving the entity resolution quality for the source combinations that have the most downstream usage. The platform team is five engineers; this is a mid-level IC role with significant breadth.

Responsibilities

  • Build and maintain data ingestion adapters for government portal APIs and bulk downloads
  • Improve entity resolution across inconsistent identifier schemes in civic datasets
  • Develop data quality scoring that flags low-reliability sources to downstream consumers
  • Handle upstream format changes and API deprecations for 20-30 active integrations
  • Design schema normalization for new data source categories
  • Monitor adapter health and respond to ingestion failures

Requirements

  • 3+ years in data engineering with multi-source integration experience
  • Strong Python, SQL, and Spark skills for data pipeline development
  • Experience with schema normalization and entity resolution techniques
  • Familiarity with government open data formats: Socrata, CKAN, ArcGIS REST APIs
  • Ability to handle ambiguous, poorly documented data sources pragmatically

Benefits

  • Fully remote with flexible schedule
  • Health, dental, and vision insurance
  • $3,000 annual professional development budget
  • Meaningful civic impact through better government data
  • 401(k) with match

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Categories

Automation & AI Workflows AI Product & Strategy

Skills

python spark sql airflow docker

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

Automation & AI Workflows AI Product & Strategy

Skills

python spark sql airflow docker aws

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