SUPPLY CHAIN DATA ENGINEER II

TE Connectivity is a company that focuses on creating a safer, sustainable, and more connected world. They are seeking a hands-on Data Engineer to build and support modern Supply Chain data products, focusing on data pipelines, analytics, and reporting across various supply chain functions.

Responsibilities:

• Work closely with the Data Engineering Manager to understand requirements and deliver assigned backlog items
• Build and maintain ELT pipelines and data models in Databricks using Delta Lake and dbt
• Ingest and harmonize SAP data (MM, IM, PP, LE) for analytics and reporting use cases
• Develop KPI datasets and dashboards related to supplier performance, inventory health, production schedules, and logistics visibility
• Perform data analysis to support Supply Chain decision-making
• Prepare ML-ready datasets and support Data Science teams with feature creation
• Support basic AI/ML and Agentic AI initiatives (data preparation, monitoring, automation support)
• Ensure data quality checks, documentation, and adherence to data governance standards

Requirements:

• Bachelor's degree in Computer Science, Data Engineering, Analytics, or related field
• 3–5 years of experience in Data Engineering or Analytics roles
• Strong hands-on experience with Databricks, SQL, Python
• Experience working with SAP data (MM, IM, PP, Logistics)
• Experience with Power BI or Tableau
• Exposure to MLflow, feature stores, or ML pipelines
• Basic understanding of AI/ML or GenAI concepts
• Agile/Scrum working experience