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Tier-1 brand, popular Data Engineer title, metro locations, and broad skill requirements increase competition.
Core data engineering skills are transferable across industries despite Azure/Microsoft Fabric emphasis.
Multiple mandatory cloud, PySpark, SQL, and platform skills create rigid technical filters.
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Design, develop, and maintain scalable ETL/ELT data pipelines leveraging Python, PySpark, SQL, Azure Data Factory, Databricks, and Microsoft Fabric.
Build and support modern data architectures using medallion architecture on Azure Data Lake Storage or OneLake for large-scale structured and unstructured data.
Collaborate with cross-functional teams including Power BI developers, data analysts, data scientists to ensure data quality, integration, and analytic enablement throughout the SDLC.
Proven expertise in Python, PySpark, SQL, Azure Data Factory, Azure Databricks, and Microsoft Fabric for data engineering.
Experience with designing and implementing ETL/ELT pipelines and medallion architecture using Delta Lake in cloud environments (Azure).
Graduate or Postgraduate degree in Computer Science or related field, or demonstrated equivalent experience.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in building and managing scalable cloud data pipelines and architectures with a focus on Azure cloud services and distributed computing (Spark).
Skilled in collaborating across analytics, BI, and product teams to integrate data for reporting and business insights.
Familiar with software development lifecycle processes including coding best practices, code reviews, testing, and deployment in agile environments.