Data Engineer

Job Title

Experience

Key Responsibilities:

• Design and build robust, reusable Python-based ETL pipelines to process data from enterprise systems (e.g., SAP, OCPLM, etc). 
• Clean and transform raw data for downstream use in analytics, ML, and visualization tools. 
• Collaborate with analytics teams to enable predictive and prescriptive models for supply chain operations. 
• Contribute to data automation efforts using Python or cloud-native scheduling tools. 
• Work with cloud technologies, especially Azure Data Lake and Databricks, to scale and operationalize workflows. 
• Ensure data integrity, quality, and traceability through every step of the pipeline. 
• Stay updated with AI/ML techniques and support model readiness with structured data. 

Required Skills & Qualifications:

• 2–4 years of experience in data engineering or analytical programming roles. 
• Strong programming skills in Python for data transformation and automation. 
• Good command over SQL for querying and joining large datasets. 
• Familiarity with Azure Data Lake, Databricks, or similar cloud platforms. 
• Solid analytical thinking and problem-solving ability in working with complex, real-world datasets. 
• Understanding of ML concepts like regression, classification, forecasting (hands-on not mandatory). 
• Ability to understand enterprise data structures from systems like SAP or OCPLM, even without direct system access. 

Tools & Technologies:

• Python, Pandas, NumPy, SQL 
• Azure Data Lake, Databricks 
• ML libraries: scikit-learn, XGBoost (as needed) 

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