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Tier-1 brand plus metro location but Databricks specialization limits applicant pool.
Databricks, Spark and cloud data engineering skills are highly transferable across industries.
Mandatory Databricks, Spark, Delta Lake and cloud skills enforce technical filtering despite no explicit years requirement.
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Design, develop, and optimize scalable data workflows and notebooks on Databricks platform, ingesting and transforming data for data lakes.
Build and maintain efficient data processing workflows using Spark (PySpark or Spark SQL), ensuring data quality, integrity, and security.
Collaborate with stakeholders to translate data requirements into technical solutions and develop data models supporting reporting and analytics.
Experience designing, implementing, and maintaining data solutions on Databricks.
Proficiency with 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.
Experienced in data modernization and migration projects utilizing Databricks and Spark at an enterprise scale.
Skilled in translating business data requirements into technical data engineering solutions with a focus on scalable and performant data workflows.
Familiar with DevOps principles and best practices in data engineering, with a history of working across technical and business teams.