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Generic senior title, Pune metro location, and hybrid setup increase applicant density moderately.
Highly domain-specific Databricks, Spark, Lakehouse skills limit cross-industry transferability.
Mandatory 8+ years, Databricks/Spark/Azure expertise and data platform experience make filters stringent.
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Design and build scalable data platforms and end-to-end data solutions involving ingestion, transformation, storage, and presentation layers.
Develop and optimize ETL/ELT pipelines using Databricks, Spark, and cloud-native technologies while implementing Lakehouse architectures following Medallion principles.
Lead architecture discussions to ensure scalability, reliability, security, efficiency; mentor junior engineers and enforce engineering standards.
8+ years of experience in Data Engineering or Data Platform development.
Strong hands-on experience with Databricks, Apache Spark, Python, and SQL.
Experience designing and implementing modern Lakehouse architectures and Medallion data models.
Location requirement: Hybrid work model based in Pune.
Experienced in building scalable enterprise data platforms with expertise in distributed data processing, data modeling, and performance optimization.
Demonstrated technical leadership skills including system design, code review, and team mentorship.
Familiar with data governance, security frameworks (RBAC, RLS, CLS), and integrating AI capabilities into data platforms.