Staff Data Engineer

Job Description SummaryThe Commercial Engine Services Business Intelligence (BI) team is building the next generation of analytics and AI-powered solutions for supply chain and commercial operations. We're looking for a Staff Data Engineer to design, build, and maintain production data pipelines that transform raw operational data into trusted, analytics-ready datasets powering our enterprise applications.
This is a hands-on data engineering role focused on building reliable and scalable data pipelines. You'll work closely with our BI Developers and Software Engineers to implement multi-layer transformation pipelines, establish data quality frameworks, optimize pipeline performance, and ensure data freshness for real-time and batch analytics.
Job Description
Roles and Responsibilities:
Data Pipeline Development & Maintenance
Build production-grade data pipelines that transform raw operational data into analytics-ready datasets for applications, reports, and AI/ML models
Implement multi-layer transformation logic following medallion architecture; write efficient code for data cleaning, enrichment, aggregation, and business logic implementation
Develop and maintain incremental loading patterns, schema evolution handling, and data versioning strategies that ensure pipeline reliability and backward compatibility
Schedule and orchestrate automated data refreshes by building automated pipelines for real-time reporting.
Optimize pipeline performance for large datasets; implement partitioning, caching, indexing, and aggregation strategies that meet dashboard performance requirements.
Troubleshoot and resolve data pipeline failures, data quality issues, and performance bottlenecks; implement fixes and preventive measures to reduce future incidents
Data Quality & Validation
Build automated data quality checks including null validation, range checks, referential integrity, business rule enforcement, and schema drift detection
Implement data validation frameworks that catch data issues early in the pipeline before they affect downstream dashboards or models
Monitor data quality metrics and alerts; investigate anomalies, communicate issues to stakeholders, and coordinate remediation with source system owners
Create data quality monitoring systems and reports that provide visibility into pipeline health, data freshness, record counts, and quality trends over time
Document known data quality issues, workarounds, and resolution plans; maintain data quality knowledge base for the BI team
Implement monitoring and alerting for data pipelines—tracking failures, data freshness, quality issues, compute costs, and execution times
Conduct root cause analysis for data incidents; document findings and implement preventive measures
Collaboration & Data Support
Partner with BI analysts to understand data requirements for dashboards and reports; translate business logic into transformation code
Collaborate with software engineers to prepare training datasets, build feature pipelines, and ensure data quality for forecasting and machine learning models
Work with Data Platform Architect to implement architectural patterns, follow coding standards, and adopt platform capabilities (data cataloging, monitoring frameworks, CI/CD pipelines)
Support the BI team with data questions, query optimization, and troubleshooting; provide guidance on how to query datasets efficiently
Coordinate with CDAIO team on source system integrations, data contracts, and ingestion layer requirements
Documentation & Best Practices
Write clear, comprehensive documentation for all data pipelines—business logic, transformation steps, data lineage, dependencies, refresh schedules, and SLAs
Create data dictionaries for datasets—column definitions, data types, expected values, refresh frequency, and usage examples
Document data quality rules, validation logic, and known issues; maintain runbooks for common troubleshooting scenarios
Follow software engineering best practices including version control (Git), code review, automated testing, and CI/CD integration
Contribute to reusable SQL/Python utilities, templates, and patterns that accelerate pipeline development across the team
Required Qualifications:
Bachelor's Degree in Computer Science, Information Systems, or related field from an accredited college or university (or a high school diploma / GED with a minimum of 4 years of relevant data engineering experience)
Minimum of 5 years of hands-on experience building data pipelines and ETL/ELT processes in production environments
Desired Characteristics
Technical Expertise
SQL Mastery: Expert-level SQL skills including complex joins, window functions, CTEs, aggregations, and query optimization; able to write efficient queries for large datasets
Python & PySpark: Solid Python programming skills and familiarity with PySpark DataFrame API, transformations, actions, and optimization techniques
Data Pipeline Development: Proven experience building ETL/ELT pipelines on cloud data platforms (Databricks, Snowflake, AWS Glue, or similar)
Data Modeling: Understanding of dimensional modeling, slowly-changing dimensions, aggregate tables, and analytics-optimized data structures
Data Quality Engineering: Experience implementing automated data validation, schema checks, and data quality frameworks
Cloud Platforms: Familiarity with cloud data services; understanding of compute optimization and cost management
Version Control & CI/CD: Experience with Git workflows, code review practices, and automated testing for data pipelines
Domain & Problem-Solving
Experience working with supply chain, manufacturing, maintenance, contracts, or similar domains is a strong plus
Demonstrates initiative to explore alternate pipeline approaches using clear tradeoff analysis
Comfortable working with ambiguous requirements; asks clarifying questions and validates assumptions with stakeholders
Stays current on modern data engineering patterns
Collaboration & Communication
Strong written and verbal communication skills: Writes clear documentation and data dictionaries; explains data issues and tradeoffs to non-technical stakeholders
Effective collaborator: Works seamlessly with BI analysts, Data Platform Architect, and AI/ML engineers
Business-minded: Asks about application usage, data requirements, and business impact; builds pipelines that solve real operational needs
Continuous learner: Self-driven to improve SQL/Python skills, learn new tools, and adopt modern data engineering best practices
Please note: This posting indicates that the position is onsite at our Evendale, OH Campus. However, this role is eligible for fully remote arrangements across the United States.
The base pay range for this position is $112,000-150,000. The specific pay offered may be influenced by a variety of factors, including the candidate’s experience, education, and skill set. This position is also eligible for an annual discretionary bonus based on a percentage of your base salary/ commission based on the plan. This posting is expected to close on Friday October 2nd, 2026.
GE Aerospace offers comprehensive benefits and programs to support your health and, along with programs like HealthAhead, your physical, emotional, financial and social wellbeing. Healthcare benefits include medical, dental, vision, and prescription drug coverage; access to a Health Coach from GE Aerospace; and the 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, as well as access to Fidelity resources and planning consultants. Other benefits include tuition assistance, adoption assistance, paid parental leave, disability insurance, life insurance, and paid time-off for vacation or illness.
GE Aerospace (General Electric Company or the Company) and its affiliates each sponsor certain employee benefit plans or programs (i.e., is a “Sponsor”). Each Sponsor reserves the right to terminate, amend, suspend, replace or modify its benefit plans and programs at any time and for any reason, in its sole discretion. No individual has a vested right to any benefit under a Sponsor’s welfare benefit plan or program. This document does not create a contract of employment with any individual.
This role will require in-person attendance for New Hire Orientation on Day 1
Additional Information
GE Aerospace offers a great work environment, professional development, challenging careers, and competitive compensation. GE Aerospace is an Equal Opportunity Employer