Senior Knowledge Graph Engineer for AI Platform & Growth

McKinsey & Company, Inc.; Atlanta (GA); On-site; USD 176,000 - 180,000; Full time

Benefits offered by this job

Medical insurance

Dental coverage

Vision coverage

Retirement plan

Paid time off

Job summary

McKinsey & Company, Inc. seeks a Senior Knowledge Graph Data Engineer to build graph-centric data pipelines and a semantic layer powering GenAI apps.

You will design entity models, implement ingestion and enrichment, and publish data to graph stores while writing production-grade Python and maintaining CI/CD on AWS-Docker infrastructure. You will evolve taxonomies and identifiers, ensure data quality, and collaborate across regions and functions to deliver scalable knowledge graph services for

Qualifications

• Degree in CS/Engineering or equivalent experience.
• 5+ years of relevant experience in data engineering and knowledge graphs.
• Strong Python development and cloud-based data engineering with AWS.
• Experience with Docker and CI/CD pipelines.
• Excellent problem solving and cross-functional collaboration.

Responsibilities

• Build graph-centric data pipelines and a semantic data layer for GenAI applications.
• Design and evolve entity/relationship models, taxonomies, and identifiers.
• Implement ingestion, normalization, and enrichment mapping sources to graph schemas.
• Publish data to graph stores and maintain production-grade code with tests.

Skills

Python development

Data engineering

Knowledge graphs

Docker

GitHub Actions

Cross-functional collaboration

Education

CS/Engineering degree or equivalent

Tools

AWS

Relational databases

Kedro

GitHub Actions CI/CD

Job description

McKinsey & Company, Inc. seeks a Senior Knowledge Graph Data Engineer to build graph-centric data pipelines and a semantic layer powering GenAI apps.

You will design entity models, implement ingestion and enrichment, and publish data to graph stores while writing production-grade Python and maintaining CI/CD on AWS-Docker infrastructure. You will evolve taxonomies and identifiers, ensure data quality, and collaborate across regions and functions to deliver scalable knowledge graph services for