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Tier-1 brand, metro Bengaluru location, and mid-level data engineering role with common skillset increase competition.
Core data engineering skills (Spark, PySpark, Python) are transferable across industries, though consulting experience adds preference.
Explicit 5–8 years requirement plus mandatory Spark/PySpark/Python and leadership make filters stringent.
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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 to ensure technical excellence and project delivery.
Collaborate with cross-functional teams to understand requirements and ensure data quality, integrity, and security across projects.
5-8 years of experience in data services, data architecture, and data engineering.
Strong hands-on expertise in Spark, PySpark, and Python for data engineering.
Bachelor's degree required (B.Tech/M.Tech/MCA/MBA).
Experience with cloud-native data engineering platforms such as Databricks, Azure Data Engineering, or AWS is highly desirable.
Experienced in leading data engineering projects and managing data engineer teams with technical guidance and performance management.
Proficient in designing scalable data pipelines and familiar with data warehousing and ETL processes.
Comfortable working in a cross-functional, client-facing advisory environment requiring collaboration and effective communication.