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Tier-1 brand and Bangalore metro increase applicant density, but specialized Spark/Databricks manager skills moderate competition.
Core data engineering skills transferable across industries, but advisory/client-facing consulting raises domain specificity.
Explicit 9-12 years, required Spark/PySpark/Python and managerial experience make filters highly strict.
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Lead design, development, and maintenance of scalable data pipelines and architectures using Spark, PySpark, and Python.
Manage and mentor a team of data engineers, oversee project timelines, resources, and budgets for successful delivery.
Collaborate with cross-functional teams to translate business needs into technical data solutions ensuring data quality and security.
8-12 years of experience in data engineering or related roles with 3+ years in a technical managerial position.
Strong hands-on experience with Spark, PySpark, and Python for data engineering tasks.
Bachelor's degree in Engineering (B.Tech), M.Tech, MCA, or MBA.
Experience with cloud-native data engineering platforms like Databricks, Azure, or AWS preferred but not mandatory.
Senior data engineer with proven leadership capabilities managing teams and projects in data engineering environments.
Strong expertise in building scalable data pipelines with a solid understanding of data warehousing and ETL processes.
Familiarity with cloud platforms and ability to implement best practices in data engineering including code reviews and testing.