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Tier-1 employer, metro Bangalore, mid-level generalist Data Engineer with broad Azure skills increases competition.
Azure, Spark, ETL, and SQL skills are broadly transferable across industries, lowering background sensitivity.
Explicit 5–7 years plus mandatory Azure, Spark, and CI/CD requirements raise shortlisting strictness.
Design, develop, and maintain automated data pipelines and ETL processes using Microsoft Azure services including Azure Data Factory, Azure Synapse, Azure Databricks, and Azure Fabric.
Optimize data pipeline performance, scalability, and reliability in Azure environment while ensuring data quality and integrity using validation frameworks.
Manage CI/CD processes for deploying and maintaining data solutions and collaborate with cross-functional teams including data scientists and architects to meet data requirements.
Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience).
5-7 years of professional experience overall with at least 2 years in a Data Engineer or similar role involving data and ETL processes.
Strong expertise in Microsoft Azure services: Azure Data Factory, Azure Synapse, Azure Databricks, Azure Blob Storage, and Azure Data Lake Storage Gen 2.
Proficiency in SQL DML querying on modern RDBMS (e.g. SQL Server, PostgreSQL) and understanding of software engineering principles relevant to data engineering (CI/CD, version control, testing).
Experienced with Azure data ecosystem and building resilient, scalable, modular data pipelines.
Familiarity with big data technologies such as Spark, especially using PySpark or similar frameworks.
Capabilities in managing end-to-end data engineering lifecycle including documentation, troubleshooting, and deploying via DevOps pipelines in an enterprise environment.