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Mid-level 5+ years plus specialized Azure/Databricks skills drive moderate competition.
Strong Microsoft Azure and enterprise integration requirements make cross-industry transferability limited.
Mandatory 5+ years, lead experience and Azure/Databricks expertise enforce strict shortlisting filters.
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Lead design, development, and optimization of scalable Azure-based data pipelines ingesting and transforming data from Microsoft platforms, SAP, CRM, retail systems, and third-party sources.
Build and maintain enterprise-scale Medallion Architecture Data Lakes (Bronze, Silver, Gold) and integrate diverse data sources to support analytics, AI, and operational use cases.
Ensure data quality, consistency, performance tuning, and enforce governance standards while collaborating with cross-functional teams and leading the data engineering team.
At least 5 years of data engineering experience with 2+ years in a lead role.
Strong hands-on experience with Azure data services including Azure Data Factory, Azure Data Lake Storage Gen2, Azure Databricks, Azure Synapse Analytics, Microsoft Fabric, and Azure SQL.
Proven expertise in Medallion Architecture Data Lakes and PySpark/Spark for large-scale data processing.
Experience integrating data from Microsoft platforms, SAP, CRM, APIs, SaaS, and third-party sources; CI/CD experience using Azure DevOps or GitHub Actions.
Experienced in enterprise-scale data integration and modern data lakehouse architecture on Microsoft Azure ecosystem.
Capable of supporting downstream AI, analytics, microservices, and agentic use cases through optimized and governed data platforms.
Proficient in leading technical teams and managing complex data workflows in fast-paced, agile environments.