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Tier-1 brand and Bangalore metro increase candidate density, but Databricks specialization reduces applicant pool.
Databricks and cloud data engineering skills transfer across industries but need platform-specific experience.
Mandatory Databricks, Spark, Python, cloud and Delta Lake skills create strict shortlisting filters.
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Design, develop, and optimize data workflows and notebooks using Databricks to ingest, transform, and load data from various sources into a data lake.
Build and maintain scalable, efficient data processing workflows using Spark (PySpark or Spark SQL) adhering to coding standards and best practices.
Collaborate with technical and business stakeholders to convert data requirements into technical solutions and ensure data quality, integrity, security, and performance optimization.
Experience in designing, implementing, and maintaining data solutions on Databricks.
Proficient in Spark, Python and/or SQL, and Delta Lake.
Experience with at least one cloud platform (Azure, AWS, or GCP).
Bachelor’s or Master’s degree in any field. Work Experience Required: Not explicitly mentioned in the JD.
Capable of managing end-to-end data engineering projects on Databricks platform in an enterprise environment.
Strong understanding of ETL/ELT processes, data warehousing and modeling concepts for reporting and analytics.
Ability to engage with both technical teams and business stakeholders to develop aligned, scalable data solutions.