Data Engineer 3/4- Supply Chain Analytics - R10215730

Northrop Grumman is a leading technology company that offers revolutionary systems impacting lives globally. They are seeking a Principal Data Engineer to build, maintain, and optimize data pipelines for supply chain analytics, ensuring data reliability and quality while collaborating with analysts and engineers.

Responsibilities:

• Pipeline Execution: Design, code, test, and deploy production-grade data pipelines using Python/PySpark and SQL within the Databricks environment to ingest and transform Supply Chain data
• SAP Integration: Implement and maintain data extraction processes from SAP ERP systems, focusing on supply chain areas
• Data Modeling: Translate high-level design specifications into physical data models and structures, ensuring the effective implementation of dimensional data models tailored for Supply Chain analytics
• Data Reliability: Actively monitor pipeline health, troubleshoot production issues, and execute necessary fixes to ensure high data availability and accuracy for downstream reporting and analytics
• Business Translation: Partner with Senior Engineers and Supply Chain analysts to understand their data needs, assisting in translating complex business questions related to demand planning, inventory, and logistics into specific data requirements
• Quality & Governance: Adhere strictly to defined standards for data quality, security, and governance protocols, including proper documentation and adherence to established code quality practices
• This role can be performed by a level 3 (mid-career) or level 4 (senior-career) professional

Requirements:

• Must have, at minimum, a Bachelor's degree in Engineering, Computer Science, Software Engineering, or a related technical field
• Minimum of 5 years of hands-on experience in Data Engineering or a related technical field
• Minimum of 1 year of experience working in Supply Chain, Logistics, or Manufacturing domains
• Hands-on experience developing data integrations from SAP ERP systems, demonstrating a foundational understanding of relevant SAP data structures
• Proficiency in SQL and Python for data manipulation and transformation
• Direct experience with cloud-based platforms such as Databricks and AWS
• Proven experience working within a team using version control systems (e.g., Git) and following agile development practices
• Minimum of 8 years of hands-on experience in Data Engineering or a related technical field
• Strong working knowledge of dimensional modeling principles
• Familiarity with specific SAP data models and modules
• Understanding of fundamental data governance and Master Data Management (MDM) concepts