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Tier-1 brand, popular mid-level data role in Bangalore with broad tech requirements yields high competition.
Core data engineering skills like Spark, SQL, Airflow and cloud are widely transferable across industries.
Explicit 3+ years plus mandatory Spark, SQL, Airflow and cloud experience increases shortlisting strictness.
Develop and maintain automated data pipelines for ingestion, transformation, and delivery of analytics datasets.
Collaborate with senior engineers and cross-functional teams to implement data models supporting reporting and analysis.
Support data quality checks, validation, monitoring, and contribute to data reliability improvements under guidance.
3+ years of experience building, implementing, and maintaining data warehousing and analytics solutions.
Hands-on experience with distributed data processing frameworks like Spark, Hive, or Iceberg and proficiency in SQL for analytical workloads.
Working knowledge of Python, Java, or Scala for data transformation and pipeline development.
Experience with cloud platforms (preferably AWS) and data pipeline orchestration tools such as Airflow.
Experienced in building scalable data engineering solutions within large enterprise or cloud-native environments with complex data needs.
Comfortable collaborating across analytics, product, and engineering teams to translate data requirements into robust pipeline designs.
Familiarity or interest in leveraging AI-assisted tooling or building LLM-powered workflows to automate and enhance data engineering tasks.