Remote Senior AI Data Engineer - Knowledge Graph

GE Aerospace; Northern (KY); Hybrid; USD 110,000 - 145,000; Full time

Benefits offered by this job

Health benefits

Dental and vision

401(k) with company match

Tuition assistance

Paid time off

Job summary

GE Aerospace in the United States seeks a Senior AI Data Engineer to design and build the AWS-native data foundation behind our enterprise AI applications, including knowledge graphs, semantic layers, retrieval pipelines, and provenance tracking. You will shape data access patterns and guide hands-on implementation for scalable AI data structures.

You will lead data modeling, develop ingestion pipelines in Python and SQL on AWS, and mentor engineers while coordinating with security and product

Qualifications

• Bachelor’s degree in CS/Engineering or STEM field.
• 3+ years of data engineering experience.
• Experience with knowledge graphs and semantic layers.
• Strong Python and SQL skills.
• Experience with AI/ML data pipelines and LLM grounding.
• Ability to collaborate with cross-functional teams.

Responsibilities

• Knowledge Graph and Semantic Layer: lead design and evolution of knowledge graphs and ontologies.
• Data Modeling and Pipelines on AWS: build ingestion, modeling, and transformation pipelines using AWS services.
• Data Quality and Governance: align grounding quality, metadata, and lineage; ensure secure data access.
• Technical Leadership: mentor engineers and communicate tradeoffs to stakeholders.

Skills

Knowledge graphs

Semantic layer

Data modeling

Python

SQL

Cross-functional collaboration

Education

Bachelor's degree in Computer Science/Engineering or STEM field

Tools

AWS

CloudFormation/CDK

Glue

Lambda

Step Functions

S3

IAM

Bedrock

Bedrock Knowledge Bases

OpenSearch

Neptune

Python

SQL

Job description

GE Aerospace in the United States seeks a Senior AI Data Engineer to design and build the AWS-native data foundation behind our enterprise AI applications, including knowledge graphs, semantic layers, retrieval pipelines, and provenance tracking. You will shape data access patterns and guide hands-on implementation for scalable AI data structures.

You will lead data modeling, develop ingestion pipelines in Python and SQL on AWS, and mentor engineers while coordinating with security and product