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Mid-level Data Engineer in Bangalore with common title, metro location, and brand attracts high competition.
Core data engineering skills transfer across industries, though Azure/Databricks specialization mildly limits portability.
Mandatory 4+ years plus PySpark, Databricks, and Azure requirements make filtering highly strict.
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Design, develop, and optimize Azure-based ETL/ELT data pipelines using PySpark and Spark SQL in Databricks.
Build and orchestrate data workflows integrating on-premise databases with Azure cloud environments using tools like ADF and HVR/Fivetran.
Ensure data quality, governance, performance tuning, and automation within CI/CD processes for scalable and reliable data solutions.
Bachelor's degree in Computer Science, Engineering, or related field.
4+ years of hands-on data engineering experience with expertise in PySpark, Spark SQL, and distributed processing.
Strong proficiency in Azure cloud services including Azure Data Factory (ADF), Databricks, and Azure Data Lake Storage (ADLS).
Experience with SQL, data modeling, performance tuning, and version control systems like Git.
Experienced with cloud-native data engineering specifically in Azure environments, including hybrid integrations and data orchestration.
Skilled in building scalable, performant Spark jobs and managing end-to-end data pipelines with strong automation and CI/CD support.
Familiar with advanced Azure Data Services components such as Delta Lake, Unity Catalog, and orchestration tools like Airflow or ADF pipelines.