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Mid-level, popular Data Engineer role with common Azure stack and metro location increases applicant competition.
Skills in Azure, PySpark, and ETL are broadly transferable across industries.
Mandatory Azure/Databricks/PySpark/SQL skills and explicit 5-year requirement make filters strict.
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Design, develop, automate, and maintain ETL pipelines using Azure Data Factory, Azure Databricks, Python (PySpark), Azure SQL Database, and SQL Server Stored Procedures for large-scale data warehouses.
Develop and optimize ETL solutions, including data integration between source applications and Enterprise Data Warehouse with performance tuning of ETL processes and SQL queries.
Document ETL data mappings, data dictionaries, unit test plans, and troubleshoot data quality issues ensuring data governance standards are met.
Minimum 5 years of experience in data engineering or related roles.
Proficiency in Azure Data Factory, Azure Databricks, Python (PySpark), Azure SQL Database, SQL Stored Procedures, and Power BI development.
Experience with Agile methodologies and performance tuning of ETL and SQL queries.
Location requirement: Ahmedabad, Gujarat, India.
Strong hands-on expertise in end-to-end ETL pipeline development and optimization using Azure data platform technologies.
Experienced in collaborating within a data team environment addressing data quality and operational support challenges.
Skilled in documenting technical solutions and implementing data governance and testing standards.