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Big Four brand, mid-level generalist data role, and metro location increase candidate competition.
Core data engineering skills are transferable, though audit and ERP domain experience moderately bias fit.
Explicit 4-6 years plus mandatory Azure/Databricks/ADF/SQL/Python requirements make filters strict.
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Develop, maintain, and optimize scalable data pipelines and warehouses using Azure cloud services including Databricks, Data Factory, Data Lake Storage, and Synapse Analytics.
Build and manage data transformations and ensure data quality and governance using Azure Databricks notebooks and Unity Catalog.
Design and develop Power BI dashboards and reports with complex DAX and Power Query for business insights and data visualization.
4-6 years of work experience in Data Engineering.
Proficiency in SQL, Python or Pyspark, and hands-on experience with Azure Databricks, Azure Data Factory, Azure Data Lake Storage, and Azure Synapse Analytics.
Bachelor's degree in B.Tech/B.E/MCA in Computer Science or Information Technology.
Experience with ETL tools and processes; secondary skills include expertise in Power BI (DAX and Power Query).
Experienced in working with complex data integration projects involving multiple ERP systems such as SAP, Oracle, and Microsoft Dynamics.
Skilled in designing data models (star/snowflake schemas) and translating business processes into visual data representations.
Comfortable adapting to emerging technologies including Azure AI services and Microsoft Fabric, with a focus on incorporating Gen AI into business processes.