Senior AI Data Engineer

Role Overview

• The Senior Data Engineer designs and builds the AWS-native data foundation behind our enterprise AI applications — knowledge graphs, semantic layers, retrieval corpora, and the pipelines that keep them trustworthy.
• This role leads both the design strategy for how our AI systems understand enterprise data and the hands-on engineering to make it real.
• You will set the patterns the rest of the team — including citizen developers building with Agents and MCPs — follow when they access, curate, or extend our data.
• Lead the design and evolution of the knowledge graphs and ontologies powering our AI's reasoning, retrieval, and explainability.
• Align enterprise data (engineering handbooks, parts, service manuals, DMAIC records, user files) into a coherent, queryable graph with clear provenance across structured, semi-structured, and unstructured sources.
• Own the retrieval substrate — graph queries, vector indexes, and hybrid retrieval — and drive measurable improvements in grounding quality.
• 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 conceptual, logical, and physical data models for operational and analytical workloads; establish modeling standards, naming conventions, and reuse patterns.
• Build ingestion and transformation pipelines in Python and SQL using AWS services — Glue, Lambda, Step Functions, S3, Athena, OpenSearch, Neptune — and AI services such as Bedrock and Bedrock Knowledge Bases.
• Author infrastructure as code in CloudFormation (CDK welcome) and apply AWS best practices for IAM, security, cost, and observability.
• 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 and access policies, as we look to modernize for AI.
• Define data contracts, attributes, and metadata that policy engines can reason over for attribute
• and context-based access control.
• Contribute to the technical data dictionary, business glossary, and data catalog.
• Set the design direction for data and semantic modeling across the team.
• Mentor engineers and citizen developers on modeling, ontology design, and retrieval engineering.
• Communicate tradeoffs and value clearly to product, business, and executive stakeholders.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a STEM field with 3+ years of data engineering experience; OR high school diploma / GED with 7+ years of equivalent experience
• Eligibility Requirement: Legal authorization to work in the U.S. is required. We will not sponsor individuals for employment visas, now or in the future, for this job.
• 5+ years of hands-on data engineering with a track record of designing — not just implementing — data models and semantic layers
• Production experience with knowledge graphs and ontologies (Neo4j, Neptune, TigerGraph, RDF/SPARQL, or similar) and graph query languages (Cypher, Gremlin, SPARQL)
• Strong AWS proficiency required: CloudFormation (or CDK), Glue, Lambda, Step Functions, S3, IAM, Bedrock, Bedrock Knowledge Bases; OpenSearch and Neptune a plus
• Strong Python and SQL; comfort across relational, graph, vector, and document stores
• Experience supporting AI/ML or LLM systems — RAG pipelines, embeddings, eval datasets, grounding corpora
• Experience integrating data access with enterprise identity and policy systems
• Strong cross-functional collaboration and communication, including technical presentations to non-data audiences

Tech Stack

• AWS
• Neo4j
• Python
• SQL

Benefits

• Healthcare benefits include medical, dental, vision, and prescription drug coverage
• Access to a Health Coach from GE Aerospace
• Employee Assistance Program, which provides 24/7 confidential assessment, counseling and referral services
• Retirement benefits include the GE Aerospace Retirement Savings Plan, a 401(k) savings plan with company matching contributions and company retirement contributions
• Access to Fidelity resources and planning consultants
• Tuition assistance
• Adoption assistance
• Paid parental leave
• Disability insurance
• Life insurance
• Paid time-off for vacation or illness