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Specialized Databricks/PySpark skillset plus Pune metro increases competition; seniority and niche reduce applicant density.
Databricks and Azure-specific tooling moderately limit portability, making background fit sensitivity medium.
Multiple mandatory Databricks, PySpark, Delta Lake, ADF, and governance requirements indicate high shortlisting strictness.
Architect, develop, and optimize scalable data platforms and ELT/ETL pipelines on Azure using Databricks, PySpark, ADF, and SQL.
Implement complex data transformations, data quality checks, and schema validations ensuring enterprise-grade data ingestion from diverse sources including on-premise, cloud systems, and APIs.
Collaborate with cross-functional teams and stakeholders to deliver analytics-ready data models and solutions aligned with business objectives.
Strong hands-on expertise in Databricks, PySpark, Azure Data Factory (ADF), and SQL.
Experience building enterprise-grade data pipelines and modern data platforms on Azure.
Work Experience Required: Not explicitly mentioned in the JD.
Location: India - Pune (Onsite at Birlasoft Office - Hinjawadi).
Experienced with advanced Delta Lake features (ACID transactions, schema enforcement, evolution, time travel) and performance tuning on Databricks clusters.
Proficient in designing dimensional models (star/snowflake schemas) and implementing data governance frameworks using Unity Catalog with RBAC/ABAC controls.
Able to mentor junior engineers and collaborate effectively with architects, product owners, IT, and business teams to align data engineering solutions with strategic business needs.