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Tier-1 brand, mid-level generalist data role, and Bangalore metro location increase applicant competition.
Core data engineering skills are transferable across industries but consulting delivery experience raises sensitivity to background.
Explicit 5-8 years plus mandatory Spark/PySpark/Python and consulting delivery experience make filters 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, ensuring technical guidance and project delivery.
Collaborate with cross-functional teams to deliver high-quality data solutions while managing project timelines and resources.
5-8 years of experience in data engineering or related roles.
Strong hands-on experience with Spark, PySpark, and Python for data pipeline development.
Bachelor's degree in Engineering (B.Tech) or related fields; M.Tech/MCA/MBA also acceptable.
Experience with cloud-native data engineering platforms such as Databricks, Azure, or AWS is highly desirable.
Practitioner capable of leading data engineering projects with a mix of hands-on technical skills and team leadership.
Experienced in designing and implementing scalable ETL processes and data architectures for business intelligence.
Familiar with cloud services, containerization, and modern data platform ecosystems aligned with advisory and analytics delivery environments.