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AI Data Contract Enforcement Engineer

Harper Adeyemi

Full-time · Job · Chicago

About the role

Data contracts are the API specification for your data infrastructure — they define what a dataset should contain, what types the fields must be, what acceptable ranges look like, and what SLAs producers must meet. When contracts are broken silently, ML models train on garbage and dashboards report nonsense. When they're enforced automatically, data quality becomes a team sport instead of an after-incident blame game. We build the data contract enforcement layer used by 90 enterprise data teams. Your role is to maintain and extend the enforcement engine: the validation runtime that checks datasets against their contracts, the alerting system that routes violations to the right owners, and the ML-based anomaly detection that catches contract violations that don't fit any predefined rule. You'll work on a team of five engineers who think deeply about data reliability. Your immediate priority is building the violation pattern analysis system — a model that groups similar violations across datasets and surfaces structural problems rather than individual alerts.

Responsibilities

  • Maintain and extend the data contract validation runtime
  • Build ML-based anomaly detection for violations outside predefined rules
  • Implement violation pattern analysis to surface structural data quality issues
  • Design alerting routing logic that reaches the right data producers
  • Create dashboards for data quality trends across contract portfolios
  • Collaborate with enterprise clients on custom contract schema extensions

Requirements

  • 3+ years in data engineering with focus on data quality or observability
  • Strong SQL and Python skills for data pipeline development
  • Experience with data quality frameworks like Great Expectations or Soda
  • Familiarity with distributed processing frameworks like Spark
  • Analytical mindset for diagnosing systemic data quality patterns

Benefits

  • Fully remote
  • Health and dental
  • 401(k) with match
  • $2,500 professional development fund
  • Bi-annual team offsites

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Categories

MLOps & AI Infrastructure Automation & AI Workflows

Skills

python sql spark airflow docker

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

MLOps & AI Infrastructure Automation & AI Workflows

Skills

python sql spark airflow docker aws

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