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Mid-senior data engineering role with common Azure/Databricks skills across major metros, attracting many qualified applicants.
Azure, Databricks and PySpark are transferable, but proprietary P&G frameworks increase firm-specific fit.
Explicit 6–9 years and mandatory Azure, Databricks, PySpark, and DevOps create strict shortlisting.
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Design, develop, and maintain data infrastructure, pipelines, and database schemas to support business objectives.
Ensure data quality, integrity, and optimize distributed systems and data storage solutions.
Collaborate with cross-functional teams to identify and prioritize data requirements and establish best practices for data engineering.
6-9 years work experience in relevant data engineering roles.
Mandatory skills: Azure, Azure Data Factory (ADF), Azure Data Lake Storage Gen2 (ADLS2), Databricks, Python, PySpark, DevOps.
Experience with P&G frameworks such as AI Factory, Ultimate, Pygentic is required.
Locations: Pune, Mumbai, Gurgaon, Noida, Chennai, Coimbatore, Bangalore.
Proven expertise operating in cloud-native data engineering environments, specifically Azure ecosystem.
Experience managing end-to-end data pipelines and distributed data architectures for business use cases.
Demonstrated capability to implement and maintain enterprise-standard frameworks and DevOps practices in data projects.