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Tier-1 brand, mid-level generalist data role in Bangalore with common Azure skillset increases candidate competition.
Azure-based data engineering skills (ETL, Spark, SQL) are broadly transferable across industries.
Explicit 5–7 years plus Azure, Spark, and ETL experience enforces strict technical and years filters.
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Design, develop, and maintain automated data pipelines and ETL processes using Microsoft Azure services (e.g., Azure Data Factory, Synapse, Databricks, Data Lake Storage).
Optimize data pipeline performance, scalability, and reliability within the Azure environment while ensuring data quality and integrity.
Manage CI/CD processes for deployment and maintenance of data engineering solutions and collaborate with data scientists, analysts, 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 with at least 2 years as a Data Engineer or similar role involving data and ETL processes.
Strong expertise in Microsoft Azure data services, including Azure Data Factory, Azure Synapse, Azure Databricks, Azure Blob Storage, and Azure Data Lake Storage Gen 2.
Proficient in SQL querying on modern RDBMS (e.g., SQL Server, PostgreSQL) and familiar with software engineering principles including CI/CD and version control.
Experienced in developing scalable, modular, and maintainable data pipelines in cloud (Azure) environments with strong operational ownership.
Demonstrates skills in big data technologies, particularly Spark and PySpark, and knowledge of related data formats such as Parquet and Delta.
Familiar with Azure DevOps, Git workflows, and automation tools like Ansible within enterprise-scale production settings.