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We are seeking a skilled Data Engineer to design, build, and maintain scalable data solutions on the Azure platform. The ideal candidate will play a key role in developing robust data pipelines, ensuring data quality, and contributing to enterprise-wide analytics initiatives.

Key Responsibilities :

- Design and develop scalable data pipelines using Spark SQL and PySpark on Azure Databricks
- Build and orchestrate ETL workflows using Azure Data Factory (ADF)
- Develop and maintain a modern Lakehouse architecture leveraging ADLS and Databricks
- Perform data preparation tasks including data cleaning, normalization, deduplication, and data type transformations
- Collaborate with DevOps teams to deploy and manage solutions in production environments
- Monitor data pipelines, identify issues, and implement corrective actions, including root cause analysis and resolution




- Actively contribute as part of the global Analytics team, delivering data-driven insights and solutions
- Collaborate with Data Science and Business Intelligence teams to share best practices and drive innovation
- Lead data engineering projects and support cross-functional initiatives led by other team members
- Apply change management practices, including documentation, communication, and training, to support system upgrades and data migrations

Must-Have Skills :

- Robust experience with Azure ecosystem (Azure Databricks, Azure Data Factory, ADLS)
- Proficiency in PySpark and Spark SQL
- Solid understanding of ETL processes and data pipeline development
- Advanced SQL skills

📌 Data Engineer - ETL/Azure Databricks (India)
🏢 CareerVitaBLR
📍 India