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Tier-1 brand, mid-level generalist data role in Bangalore with broad Azure/Spark requirements increases competition.
Core data engineering skills transfer across industries, but Azure and Spark tooling increase domain specificity moderately.
Explicit 5–7 years requirement, mandatory Azure/ETL/Spark and CI/CD skills raise shortlisting strictness.
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Design, develop, and maintain scalable, modular, and cost-effective data pipelines and ETL processes using Microsoft Azure services such as Azure Data Factory, Azure Synapse, and Azure Databricks.
Collaborate with data scientists, analysts, and architects to deliver high-quality data solutions ensuring data quality, integrity, and pipeline performance in Azure environment.
Manage CI/CD processes, troubleshoot pipeline issues, and maintain documentation for data processes and best practices.
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 handling data and ETL.
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 with modern RDBMS (e.g., SQL Server, PostgreSQL) and familiar with software engineering principles including CI/CD and version control.
Experienced in building and optimizing Azure-based data pipelines with knowledge of big data technologies like Spark and PySpark.
Capable of managing end-to-end data engineering lifecycle including CI/CD pipeline management and troubleshooting in cloud environments.
Strong practical understanding of Azure environment management, including subscriptions, resource groups, and Azure DevOps workflows.