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Tier-1 brand, mid-level (5-8 years), metro Bangalore, and broad in-demand data engineering skills increase competition.
Core data engineering skills are transferable across industries, but consulting context adds moderate domain specificity.
Explicit 5-8 years plus mandatory Spark/Databricks certifications and specific tech stack makes shortlisting strict.
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 technical guidance and performance management.
Collaborate with cross-functional teams to understand data requirements and deliver high-quality, secure data engineering solutions while managing project timelines and budgets.
5-8 years of experience in data engineering or related roles.
Mandatory certifications: Spark 3.0 and/or Databricks Advanced/Professional Architect.
Strong hands-on experience with Spark, PySpark, Python; experience with cloud-native platforms such as Databricks, Azure Data Engineering, or AWS preferred.
Bachelor's degree required (B.Tech / M.Tech / MCA / MBA).
Proven leadership skills with experience managing data engineering teams in complex projects.
Deep expertise in building scalable data pipelines and architecture with Spark ecosystem and cloud data platforms.
Comfortable working in environments requiring managing cross-functional stakeholder relationships and overseeing project delivery timelines.