Senior Knowledge Graph Engineer for GenAI Pipelines

McKinsey & Company

Chicago (IL)

On-site

USD 176,000 - 179,500

Full time

14 days+
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Benefits offered by this job

Medical coverage
Retirement contributions program
Paid time off

Job summary

McKinsey & Company in Chicago is seeking a data engineer to design and build graph-centric data pipelines and a semantic data layer that powers GenAI applications. You will develop a platform deployed across regions and functions, combining AI capabilities, domain expertise, and human judgment.

The role requires 5+ years in data engineering, experience with AWS, Docker, Python, and knowledge graphs. You will write production-grade code with tests, implement CI/CD, and optimize data pipelines for

Qualifications

  • Degree in CS/Engineering or equivalent experience.
  • 5+ years of relevant experience in data engineering or related field.
  • Strong experience with AWS cloud-based data engineering.

Responsibilities

  • Design and evolve entity/relationship models and taxonomies.
  • Implement ingestion, normalization, and enrichment mapping sources to graph schemas.
  • Write production-grade Python code with tests; maintain CI/CD pipelines; operate AWS- and Docker-based infrastructure.

Skills

Data engineering
Python development
Knowledge graphs
Docker
AWS
Relational databases
Testing automation
CI/CD
GitHub Actions
GenAI interest
Kedro
Strong communication

Education

Degree in CS/Engineering or equivalent experience
5+ years of relevant experience

Tools

GitHub Actions
Kedro
AWS

Job description

McKinsey & Company in Chicago is seeking a data engineer to design and build graph-centric data pipelines and a semantic data layer that powers GenAI applications. You will develop a platform deployed across regions and functions, combining AI capabilities, domain expertise, and human judgment.

The role requires 5+ years in data engineering, experience with AWS, Docker, Python, and knowledge graphs. You will write production-grade code with tests, implement CI/CD, and optimize data pipelines for

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