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Broad mid-level data role in Bangalore with popular skills and a well-known startup brand increases competition.
Core data engineering skills (Spark, Python, AWS) are highly transferable across industries.
Explicit 6+ years and many mandatory data platform technologies enforce strict shortlisting.
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Design and evolve a multi-tenant, cloud-scale data platform for thousands of users focusing on tenant isolation, governance, and data quality.
Drive the modernization from batch-oriented data processing to near real-time and real-time data ingestion architectures.
Build large-scale data platforms enabling faster decision-making and new AI/ML use cases across the automotive retail ecosystem.
6+ years of experience in Data Engineering.
Strong expertise in Python, SQL, and distributed data processing frameworks such as Apache Spark.
Experience with cloud data services including AWS EMR, S3, Glue, Athena, and streaming technologies like Kafka, Flink, or Kinesis.
Deep understanding of data modeling (dimensional, Data Vault), data warehousing, lakehouse technologies (Delta Lake, Apache Iceberg, Apache Hudi), and workflow orchestration using Airflow.
Technical leader skilled in building scalable batch and real-time ETL/ELT pipelines for cloud-native multi-tenant environments.
Experienced in designing enterprise data architectures with strong focus on performance tuning, data quality frameworks, and governance.
Comfortable working with modern data engineering tools, cloud infrastructure, and implementing CI/CD and Infrastructure as Code practices.