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Tier-1 employer in Bangalore, mid-level generalist data engineering role attracts many qualified applicants.
Azure data engineering skills are highly transferable across industries, minimal energy-specific dependency.
Explicit 6–8 years plus mandatory Azure data platform, ETL, and Python/Spark skills enforce strict screening.
Design, develop, and maintain enterprise-scale data pipelines and platforms using Azure Data Factory, Azure Synapse Analytics, Microsoft Fabric, and Azure Data Lake.
Build scalable ETL/ELT frameworks and optimize data models for enterprise reporting, analytics, and AI/ML use cases.
Ensure data quality, governance, security, and collaborate with multiple teams to enable reliable and secure analytics solutions.
6-8 years of experience in data engineering, specifically with Microsoft Azure ecosystem.
Proficient in Azure Data Factory, Azure Data Lake Storage, Azure Synapse Analytics / Microsoft Fabric, Azure SQL Database, advanced SQL and data modeling.
Experience with ETL/ELT design and implementation; programming skills in Python and/or Spark.
Knowledge of data governance, security, CI/CD, Git, and cloud-native data deployment practices.
Strong experience operating within enterprise-scale cloud data platforms in Azure environment with a focus on scalability and security.
Experienced in integrating diverse enterprise data sources including APIs and systems like ServiceNow and SAP.
Capable of supporting DevOps practices and collaborating effectively with analytics and business intelligence teams, familiar with Power BI is a plus.