Back
Tier-1 brand, mid-level generalist data role in Bengaluru with broad Azure/Databricks requirements, so high competition.
Azure Databricks, ADLS Gen2, PySpark data engineering skills are highly transferable across industries.
Explicit 3–5 years plus mandatory Azure, Databricks, PySpark, SQL skills makes shortlisting strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Own and develop data engineering solutions on the Azure platform, including Azure Data Factory pipelines, Azure Databricks, and PySpark for large-scale data processing.
Implement and maintain data architectures using Delta Lake and medallion patterns, ensuring data modeling with dimensional, normalized, and flat schemas.
Manage CI/CD pipelines and version control via Azure DevOps and Git for reliable and scalable data engineering workflows.
3–5 years of hands-on data engineering experience on the Azure platform.
Proficiency in Azure Data Factory, Azure Databricks, PySpark, SQL, and Python scripting.
Experience with Azure Data Lake Storage Gen2 and Blob Storage.
Experience working with CI/CD pipelines and version control systems like Azure DevOps and Git.
Experienced in applying data modeling concepts and scalable data architecture design using Delta Lake and medallion architecture.
Comfortable working with Azure cloud native data services and automation via CI/CD.
Has exposure to or willingness to engage with streaming platforms (e.g., Apache Kafka, Azure Event Hubs) and infrastructure as code concepts.