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Strong company brand, metro Bangalore, popular senior data role, and broad multi-technology requirements.
Data engineering and cloud platform skills are broadly transferable across industries.
Explicit 7+ years requirement, extensive mandatory tech stack, and leadership responsibilities increase shortlisting strictness.
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Design, build, and maintain scalable, high-performance data pipelines and platforms for batch and real-time workloads.
Lead technical initiatives influencing data architecture, engineering standards, and best practices across the organization.
Collaborate cross-functionally with Data Science, Machine Learning, Product, and Analytics teams to enable trusted data solutions and actionable insights.
7+ years of professional experience in Data Engineering or Distributed Data Systems.
Bachelor's degree in Computer Science, IT, Engineering, or related field (or equivalent experience).
Strong hands-on skills with Python, Spark/PySpark, advanced SQL, modern cloud platforms (preferably AWS), and data warehouse technologies (e.g., Snowflake, Redshift).
Experience designing and operating scalable ETL/ELT pipelines, data modeling, and data governance best practices.
Proven technical leadership with ability to own architecture decisions and mentor engineering teams.
Experienced working in complex, multi-stakeholder environments collaborating with analytics, ML, and product teams.
Strong expertise in modern data technologies including Spark, Kafka, Airflow, cloud-native services, and data lake/warehouse platforms.