Staff Data Engineer

Staff Data Engineer role on GE Aerospace’s Commercial Engine Services BI team, building production data pipelines that power real-time and batch analytics and AI/ML.

Responsibilities

• Design and build production-grade data pipelines that convert raw operational data into analytics-ready datasets for applications, reports, and AI/ML models
• Implement multi-layer transformation logic using medallion architecture (data cleaning, enrichment, aggregation, and business logic)
• Develop and maintain incremental loading, handle schema evolution, and apply data versioning to support reliability and backward compatibility
• Schedule and orchestrate automated data refreshes for real-time reporting through automated pipeline runs
• Optimize performance for large datasets using partitioning, caching, indexing, and aggregation strategies aligned to dashboard performance requirements
• Troubleshoot pipeline failures, data quality issues, and performance bottlenecks; implement fixes and preventive measures to reduce repeat incidents
• Create automated data quality checks, including:
  • null validation, range checks, referential integrity
  • business rule enforcement
  • schema drift detection
• Implement data validation frameworks to detect issues early so downstream dashboards or models are not impacted
• Monitor data quality metrics and alerts; investigate anomalies, communicate with stakeholders, and coordinate remediation with source system owners
• Build data quality monitoring systems and reports covering pipeline health, data freshness, record counts, and quality trends over time
• Document known data quality issues, workarounds, and resolution plans; maintain a knowledge base for the BI team
• Implement monitoring and alerting for pipelines to track failures, data freshness, quality issues, compute costs, and execution times
• Perform root cause analysis for data incidents, document findings, and implement preventive actions
• Partner with BI analysts to understand dashboard and reporting needs; translate business logic into transformation code
• Collaborate with software engineers to create training datasets, feature pipelines, and supporting data quality for forecasting and machine learning models
• Work with the Data Platform Architect to follow architectural patterns, coding standards, and platform capabilities (data cataloging, monitoring frameworks, CI/CD pipelines)
• Support BI with data questions, query optimization, and troubleshooting, including guidance for efficient dataset querying
• Coordinate with the CDAIO team on source system integrations, data contracts, and ingestion layer requirements
• Produce clear documentation for pipelines, including business logic, transformation steps, data lineage, dependencies, refresh schedules, and SLAs
• Create and maintain data dictionaries (column definitions, data types, expected values, refresh frequency, and usage examples)
• Document data quality rules and validation logic; maintain runbooks for common troubleshooting scenarios
• Apply software engineering best practices including version control (Git), code review, automated testing, and CI/CD integration
• Contribute reusable SQL/Python utilities, templates, and patterns to accelerate pipeline development across the team

Requirements

• Bachelor’s Degree in Computer Science, Information Systems, or a related field from an accredited college or university
• Alternative: high school diploma / GED with minimum 4 years of relevant data engineering experience
• At least 5 years of hands-on experience building data pipelines and ETL/ELT processes in production environments
• Expert SQL skills: complex joins, window functions, CTEs, aggregations, and query optimization for large datasets
• Python programming skills and familiarity with PySpark DataFrame API (transformations, actions, optimization techniques)
• Proven experience building ETL/ELT on cloud data platforms such as Databricks, Snowflake, AWS Glue, or similar
• Understanding of dimensional modeling, slowly-changing dimensions, aggregate tables, and analytics-optimized data structures
• Experience implementing automated data validation, schema checks, and data quality frameworks
• Familiarity with cloud data services, including compute optimization and cost management
• Experience using Git workflows, code review practices, and automated testing for data pipelines

Technologies

• SQL, Python, PySpark
• Databricks, Snowflake, AWS Glue
• Git, CI/CD
• Medallion architecture, ETL, ELT

Benefits

• Healthcare benefits: medical, dental, vision, and prescription drug coverage
• Access to a Health Coach from GE Aerospace
• Employee Assistance Program (24/7 confidential assessment, counseling, and referral services)
• GE Aerospace Retirement Savings Plan (401(k) with company matching 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

Desired Characteristics

• Experience working with supply chain, manufacturing, maintenance, contracts, or related domains is a strong plus
• Initiative to explore alternate pipeline approaches using clear tradeoff analysis
• Comfort working with ambiguous requirements; asks clarifying questions and validates assumptions with stakeholders
• Stays current with modern data engineering patterns
• Writes clear documentation and data dictionaries; explains data issues and tradeoffs to non-technical stakeholders
• Works effectively with BI analysts, Data Platform Architect, and AI/ML engineers
• Self-driven to improve SQL/Python skills, learn new tools, and adopt modern data engineering best practices

Work Location / Remote Eligibility

• Onsite at the Evendale, OH campus
• Eligible for fully remote arrangements across the United States
• In-person attendance required for New Hire Orientation on Day 1

Pay / Posting Details

• Base pay range: $112,000 to $150,000 per year
• Eligible for an annual discretionary bonus based on a percentage of base salary (or commission based on the plan)
• Expected posting close date: Friday, October 2, 2026

Relocation

• Relocation assistance provided: No