Note: The job is a remote job and is open to candidates in USA. GE Aerospace is seeking a Staff Data Engineer for its Commercial Engine Services Business Intelligence team. The role designs, builds, and maintains scalable production data pipelines that transform operational data into trusted datasets for enterprise applications, analytics, and AI/ML models, while establishing data quality, monitoring, documentation, and performance optimization practices.
Responsibilities
- 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
- 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
- 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
- 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
Skills
- 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
- Expert-level SQL skills including complex joins, window functions, CTEs, aggregations, and query optimization; able to write efficient queries for large datasets
- Solid Python programming skills and familiarity with PySpark DataFrame API, transformations, actions, and optimization techniques
- Proven experience building ETL/ELT pipelines on cloud data platforms (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; understanding of compute optimization and cost management
- Experience with Git workflows, code review practices, and automated testing for data pipelines
- 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
- Writes clear documentation and data dictionaries; explains data issues and tradeoffs to non-technical stakeholders
- Works seamlessly with BI analysts, Data Platform Architect, and AI/ML engineers
- Asks about application usage, data requirements, and business impact; builds pipelines that solve real operational needs
- Self-driven to improve SQL/Python skills, learn new tools, and adopt modern data engineering best practices
- GE Aerospace will only employ those who are legally authorized to work in the United States for this opening
- Experience working with supply chain, manufacturing, maintenance, contracts, or similar domains is a strong plus
- Strong written and verbal communication skills
Benefits
- Medical, dental, vision, and prescription drug coverage
- Access to a Health Coach from GE Aerospace
- Employee Assistance Program, providing 24/7 confidential assessment, counseling and referral services
- GE Aerospace Retirement Savings Plan
- 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
- Annual discretionary bonus based on a percentage of base salary
- Commission based on the plan
- Fully remote arrangements across the United States
Company Overview