Senior Data and AI Engineer

Gulf Coast Automation Group•Chicago, IL
•Hybrid

About The Position

This is a hands-on, direct-hire Senior Data and AI Engineer role with a manufacturing-industry client in downtown Chicago. The position is hybrid, with onsite work three days a week. The engineer will turn data and analytics concepts into reliable production capabilities by building scalable data products, pipelines, APIs, and machine learning and AI solutions that support measurable business outcomes. Manufacturing experience is ideal, but curious engineers with strong business acumen are encouraged to apply.

Requirements

  • Five or more years of experience in data engineering, machine learning engineering, software engineering, analytics engineering, or a related technical field.
  • Strong Python development skills.
  • Advanced SQL skills, including experience with analytical data models and ETL or ELT pipelines.
  • Experience delivering production solutions on modern cloud data platforms.
  • Experience integrating data from multiple enterprise systems.
  • Knowledge of REST APIs, Git, automated testing, CI/CD, code review, and the full development-to-production lifecycle.
  • Authorization to work in the U.S. without current or future visa sponsorship.

Nice To Haves

  • Experience with Snowflake, dbt, FastAPI, Azure, Terraform, MLOps, Generative AI, or manufacturing and supply chain data.
  • Manufacturing experience.
  • Strong business acumen.

Responsibilities

  • Design, build, test, and maintain scalable data pipelines, transformations, analytical models, and reusable data products using Python, SQL, Snowflake, and dbt.
  • Develop Python applications, APIs, and data services that connect enterprise data and models with downstream applications and workflows.
  • Productionize machine learning, forecasting, optimization, and AI solutions, including deployment, monitoring, versioning, and retraining.
  • Implement automated testing, data-quality controls, CI/CD, Infrastructure as Code, monitoring, and other modern engineering practices.
  • Partner with data scientists, analysts, engineers, and business stakeholders to translate requirements into maintainable solutions and resolve production issues.
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