Remote Senior AI Data Engineer

GE Aerospace; Redmond (WA); Remote; USD 110,000 - 145,000; Full time

Job summary

GE Aerospace is seeking a Senior Data Engineer to design the AWS-native data foundation for enterprise AI, including knowledge graphs, semantic layers, and retrieval pipelines. You will shape data access, provenance, and trust across structured and unstructured sources while enabling citizen developers and AI engineers.

You will lead data modeling, governance, and production pipelines using Python/SQL on AWS, with a focus on grounding quality and scalable infrastructure across the enterprise.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a STEM field
• At least three years of data engineering experience

Responsibilities

• Design and evolve knowledge graphs and ontologies for AI reasoning and explainability
• Align enterprise data into a coherent, queryable graph with provenance across sources
• Own the retrieval substrate and drive improvements in grounding quality
• Curate grounding corpora, eval datasets, and retrieval benchmarks for LLM features
• Instrument metrics for retrieval quality, grounding accuracy, and freshness
• Shape training and inference data contracts with AI engineers
• Model data conceptually, logically, and physically for operational and analytical workloads
• Build ingestion and transformation pipelines in Python and SQL on AWS
• Collaborate with security and policy teams on data access contracts
• Mentor engineers on modeling and retrieval engineering
• Communicate tradeoffs to product and executive stakeholders

Skills

Knowledge graphs

AWS

Python

SQL

AI/ML data

Data modeling

Data governance

Education

Bachelor's degree in Computer Science, Engineering, or STEM

Tools

Neo4j

Neptune

TigerGraph

RDF/SPARQL

Cypher

Gremlin

OpenSearch

Bedrock

Bedrock Knowledge Bases

CloudFormation/CDK

Glue

Lambda

Step Functions

S3

IAM

Job description

GE Aerospace is seeking a Senior Data Engineer to design the AWS-native data foundation for enterprise AI, including knowledge graphs, semantic layers, and retrieval pipelines. You will shape data access, provenance, and trust across structured and unstructured sources while enabling citizen developers and AI engineers.

You will lead data modeling, governance, and production pipelines using Python/SQL on AWS, with a focus on grounding quality and scalable infrastructure across the enterprise.