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Open nowPosted yesterday

Staff Data Engineer

GE Aerospace126 open roles

Pay
$112,000 – $150,000 a year
Where
Evendale
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Your applicationOpen nowStaff Data EngineerGE Aerospace · Evendale

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The clock on this job

Early applications get read.

7.7% of postings close within 7 days. Measured by our own scanner across the market. GE Aerospace postings stay open a median of 1 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.3%3 days
  3. 7.7%7 days
  4. 14.0%14 days
  5. 33.7%30 days
This job: posted yesterday

GE Aerospace median: 1 days open

The posting

Job Description Summary

The 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. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.

GE Aerospace will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable). Employees may also be subject to random and reasonable-suspicion drug and alcohol testing.

Relocation Assistance Provided: No

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