Job Description SummaryResponsible for managing business critical data engineering processes and data architecture solutions in order to enable analytical and reporting solutions. Responsible for analyzing and preparing the data needed for data science based outcomes. Also responsible for managing and maintaining metadata data structures besides providing necessary support for post-deployment related activities. Accountable to deliver results in a timely manner using agile methodologies.
Job Description
Job Overview:
As a Supply Chain Data Engineer for the GE Aerospace Digital Workplace team, you will be responsible for designing, building, and maintaining the data and analytics solutions that power Digital Workplace supply chain decisions. Working under the leadership of our Data & Analytics Leader, this role oversees end to end data pipelines and reporting for key operational metrics such as PC and accessory volumes, open PC returns, inventory levels, delivery performance, and deployment trends. The successful candidate will partner closely with Supply Chain, Digital Workplace Operations, Finance, and regional stakeholders to provide accurate, timely, and actionable insights that improve service levels, optimize inventory, and reduce total cost. This position is crucial for driving improvements in our digital workplace environment, ensuring seamless reporting across our organization. You will be part of a growing, focused team to continually develop this internal product portfolio, delivering increased value to our 70,000+ user base across the world, impacting every employee across the company.
Essential 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.
Minimum Qualifications:
- 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
- Note: Military experience is equivalent to professional experience
Desired Characteristics:
- 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 w