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Tier-1 brand, mid-level Data Engineer title, Bangalore location and broad Azure skillset increase applicant competition.
Strong core data engineering skills transfer across industries, though energy/OT experience raises domain specificity.
Mandatory 6–8 years plus specific Azure, ETL, SQL, Python, and governance expertise makes shortlisting highly strict.
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 to process structured and unstructured data, ensuring data quality, governance, security, and compliance.
Collaborate with business, analytics, and engineering teams to deliver reliable, secure, and scalable data solutions supporting analytics, reporting, and AI/ML use cases.
6-8 years of experience in data engineering with enterprise-scale data platforms.
Strong experience with Azure Data Engineering services: Azure Data Factory, Azure Data Lake Storage, Azure Synapse Analytics or Microsoft Fabric, and Azure SQL Database.
Advanced SQL, data modelling, and ETL/ELT design and implementation skills; proficiency in Python and/or Spark for data processing.
Experience integrating APIs and enterprise data sources, knowledge of data governance, security frameworks, and cloud-native deployment with Git and CI/CD.
Experienced working in cloud-native Microsoft Azure ecosystems with strong data platform design and optimization skills for large datasets.
Capable of working across global teams to support diverse business and analytics requirements, indicating adaptability to enterprise environments.
Familiarity or working knowledge of Power BI and AI/ML use cases, supporting collaboration with analytics and business intelligence teams.