Staff Data & Analytics Engineer

GE Aerospace is a leading company in the aviation sector, and they are seeking a Staff Data & Analytics Engineer to manage critical data engineering processes and support analytical solutions. The role involves designing and maintaining data pipelines, ensuring data quality, and collaborating with cross-functional teams to provide actionable insights for supply chain decisions.

Responsibilities:

• Design, build, and maintain scalable ETL/ELT data pipelines integrating data from asset management, logistics, ticketing, ERP, and procurement systems
• Develop and manage data models and integrations for Digital Workplace supply chain domains, including PCs, accessories, orders, deliveries, returns, and inventory
• Ensure data quality and governance by implementing validation rules, monitoring, and data standards that keep key datasets accurate, complete, and consistent
• Own core dashboards and reports for PC and accessory volumes, open returns and aging, inventory coverage, delivery times vs SLA, and PC deployment trends
• Analyze trends and performance to identify bottlenecks, risks, and improvement opportunities across the Digital Workplace supply chain, providing clear recommendations to stakeholders
• Partner with cross-functional teams (Supply Chain, Procurement, Digital Workplace Operations, Finance, regions) to translate business needs into data solutions and align on metrics and definitions
• Automate and optimize data and reporting processes to reduce manual effort, improve reliability, and expand self-service analytics capabilities
• Document and promote best practices for data engineering, including version control, testing, monitoring, and knowledge sharing for pipelines, models, and reports
• Communicate effectively both within immediate team, horizontal partners, and GE Aerospace leadership

Requirements:

• Bachelor's degree from accredited university or college with minimum of 4 years of professional experience OR Associates degree with minimum of 7 years of professional experience OR High School Diploma with minimum of 9 years of professional experience
• A minimum of 5 years of professional experience in the Data and Analytics domain
• A minimum of 2 years of professional experience in Digital Workplace Technology
• Strong SQL and data modeling skills, with experience extracting, joining, and shaping large operational datasets (orders, shipments, inventory, returns, deployments)
• Proficiency with scripting languages (e.g., Python or R) to build and automate ETL/ELT jobs, data validation routines, and analytical workflows
• Hands-on experience with data warehousing or lakehouse platforms, including designing efficient schemas and optimizing query performance for supply chain analytics
• Applied analytics experience using statistical methods and basic forecasting to analyze demand, lead times, inventory coverage, and delivery performance
• Background in supply chain, logistics, or asset lifecycle processes, ideally including order-to-delivery, returns, and inventory management concepts
• Experience with integration and monitoring tools (e.g., APIs, message queues, or platforms like ServiceNow/Splunk) to connect supply chain data with operational workflows
• Excellent problem-solving and analytical skills, able to translate ambiguous business questions into data requirements and clear, actionable insights
• Strong communication and data storytelling ability, including explaining complex data findings to non-technical stakeholders in Supply Chain, Finance, and Operations
• Proven collaborator in cross-functional, agile environments, comfortable working with procurement, logistics partners, Digital Workplace teams, and regional stakeholders
• Demonstrated ownership and continuous improvement mindset, proactively identifying data quality issues, removing obstacles, and driving automation and standardization of reporting