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High due to Tier-1 employer, metro Bangalore location, popular data-engineering manager role, and broad technical requirements.
Medium because core data engineering skills transfer across industries, though advisory consulting experience is preferred.
High because the JD mandates explicit 9-12 years plus mandatory Spark/PySpark/Python and cloud/databricks skills.
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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, ensuring delivery of high-quality data solutions aligned with business needs.
Oversee project timelines, resources, and budgets to successfully deliver data engineering engagements, incorporating cloud-native platforms like Databricks, Azure, or AWS.
8-12 years of experience in data engineering or related roles, including 3+ years in a technical managerial role.
Strong hands-on expertise with Spark, PySpark, and Python for data engineering tasks.
Experience with cloud-native data engineering platforms such as Databricks, Azure Data Engineering, or AWS.
Educational qualification: B.Tech / M.Tech / MCA / MBA.
Experienced senior data architect comfortable leading technically complex data engineering projects and teams.
Proficient in building scalable data pipelines and applying data warehousing and ETL best practices.
Able to collaborate cross-functionally to translate business needs into technical data solutions and manage project delivery end-to-end.