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Tier-1 brand, mid-level generalist data engineer in Bangalore with common Spark/Python skills increases competition.
Core data engineering skills (Spark, Python, cloud) are highly transferable across industries.
Explicit 5-8 years requirement plus mandatory Spark/PySpark/Python skills increases shortlisting strictness.
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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 high-quality delivery of data engineering projects.
Collaborate with cross-functional teams to translate business needs into technical data requirements and oversee project timelines, resources, and budgets.
5-8 years of work experience in data engineering or related roles.
Strong hands-on expertise in Spark, PySpark, and Python for data engineering.
Bachelor's degree in Engineering (B.Tech) or related fields such as M.Tech, MCA, or MBA.
Experience with cloud-native data engineering platforms (Databricks, Azure, or AWS) is highly desirable.
Experienced in managing and leading data engineering teams with technical and performance management responsibilities.
Skilled in designing and building scalable, high-quality data pipelines and architectures with emphasis on Spark and cloud platforms.
Familiarity with advanced data engineering tools, including cloud storage/processing services, containerization (Docker, Kubernetes), and data visualization, to drive innovative data solutions.