Back
Mid-level, popular data role in Bangalore with broad stack requirements increases applicant competition.
Core data engineering skills are highly transferable across industries despite automotive domain context.
Explicit 6+ years plus mandatory Spark, AWS, streaming, and lakehouse skills create strict filters.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, build, and evolve a multi-tenant, cloud-scale enterprise data platform supporting thousands of dealerships and business users with tenant isolation, governance, and data quality.
Drive transition from batch-oriented to near real-time and real-time data ingestion architectures for faster decision-making and AI/ML enablement.
Develop scalable batch and real-time ETL/ELT pipelines using modern data engineering frameworks and tools.
6+ years of experience in Data Engineering.
Strong expertise in Python, SQL, Apache Spark, and AWS services including EMR, S3, Glue, and Athena.
Experience with batch, streaming, and CDC-based data ingestion pipelines using technologies like Kafka, Flink, or Kinesis.
Deep knowledge of data modeling (dimensional modeling, Data Vault), data warehousing, lakehouse technologies (Delta Lake, Apache Iceberg, or Apache Hudi), and workflow orchestration tools such as Airflow.
Experienced in building and scaling large data platforms with multi-tenant architecture in cloud environments.
Skilled in implementing real-time streaming data pipelines and integrating data quality and monitoring frameworks.
Comfortable tackling complex data challenges combining batch and streaming data for enterprise analytics and AI use cases.