AI Data Engineer: Knowledge Graphs & AWS Pipelines

GE Aerospace; Madisonville (KY); Remote; USD 110,000 - 145,000; Full time

Job summary

GE Aerospace seeks a Senior Data Engineer to design the AWS-native data foundation behind our enterprise AI applications, including knowledge graphs, semantic layers, and retrieval pipelines. You will lead design strategy and hands-on engineering to make the data accessible, citable, and trustworthy across teams.

You will build data models, ingest and transform data with Python and SQL on AWS services (Glue, Lambda, Step Functions, S3, OpenSearch, Neptune), and define data contracts for AI

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a STEM field.
• Minimum of three years of data engineering experience.
• Five+ years of hands-on data engineering with data modeling and semantic layers.
• Production experience with knowledge graphs and ontologies (Neo4j, Neptune, TigerGraph, RDF/SPARQL, or similar).
• Strong AWS proficiency: CloudFormation/CDK, Glue, Lambda, Step Functions, S3, IAM, Bedrock, Bedrock Knowledge Bases; OpenSearch and Neptune a plus.
• Strong Python and SQL; experience with relational, graph, vector, and document stores.
• Experience supporting AI/ML or LLM systems — RAG pipelines, embeddings, eval datasets, grounding corpora.

Responsibilities

• Lead the design and evolution of knowledge graphs and ontologies powering AI reasoning, retrieval, and explainability.
• Align enterprise data into a coherent, queryable graph with provenance across sources.
• Own the retrieval substrate — graph queries, vector indexes, and hybrid retrieval.
• Curate grounding corpora, eval datasets, and retrieval benchmarks for LLM-based features.
• Instrument metrics for retrieval quality, grounding accuracy, and freshness; drive regressions down over time.
• Shape training and inference data contracts with AI engineers, including feedback loops from user signals.
• Produce data models for operational and analytical workloads; establish modeling standards and reuse patterns.
• Build ingestion and transformation pipelines in Python/SQL using AWS services — Glue, Lambda, Step Functions, S3, Athena, OpenSearch, Neptune; and Bedrock services.
• Author infrastructure as code in CloudFormation (CDK welcome) and apply AWS security, cost, and observability best practices.
• Profile sources, identify data quality gaps, and design automated validation, monitoring, metadata, and lineage.
• Partner with security and platform teams to integrate data access with enterprise identity policies; define data contracts and metadata for policy engines.
• Contribute to the data dictionary, business glossary, and data catalog.
• Set the design direction for data and semantic modeling; mentor engineers and citizen developers.

Skills

Knowledge graphs

AWS proficiency

Python

SQL

Data modeling

Stakeholder communication

Education

Bachelor's degree in CS/Engineering

Tools

Neo4j

Neptune

TigerGraph

RDF/SPARQL

Cypher

Gremlin

OpenSearch

Bedrock

CloudFormation/CDK

Job description

GE Aerospace seeks a Senior Data Engineer to design the AWS-native data foundation behind our enterprise AI applications, including knowledge graphs, semantic layers, and retrieval pipelines. You will lead design strategy and hands-on engineering to make the data accessible, citable, and trustworthy across teams.

You will build data models, ingest and transform data with Python and SQL on AWS services (Glue, Lambda, Step Functions, S3, OpenSearch, Neptune), and define data contracts for AI