Mandatory skills |
- 7–9 years of experience in data architecture, data modeling, data engineering, and data governance.
- Proven expertise in Kimball modeling techniques, dimensional modeling, and data warehouse design.
- Strong understanding of ISA-95, Industry 4.0, and maintenance strategies in manufacturing or industrial sectors.
- Hands-on experience with Azure Data Factory, Azure Databricks, Azure Data Lake, and related cloud-native data services.
- Proficiency in SQL and Python for data transformation, automation, and querying.
- Experience working with REST APIs to integrate external data sources.
- Familiarity with ETL/ELT processes, data integration tools, and data pipeline orchestration.
- Exposure to SAP, production and operations data, time-series data, and engineering data.
- Experience with ML model integration, GenAI, and LLM-based analytics is a plus.
- Strong communication and stakeholder management skills, with the ability to work in agile teams and participate in sprint ceremonies.
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Desired skills |
- Kimball Data Modeling, Dimensional Modeling, Star Schema, Fact and Dimension Tables, Slowly Changing Dimensions (SCD), Data Warehouse Design,Data Vault Modeling, Conceptual, Logical, and Physical Data Models, Enterprise Data Modeling, Data Modeling Tools (e.g., ER/Studio, Erwin, PowerDesigner)
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