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Niche senior data engineering skills reduce competition despite Bangalore metro location.
Data engineering skills and tools are broadly transferable across industries.
Multiple mandatory technologies and leadership expectations create strict technical screening.
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Lead design and development of scalable data pipelines and workflows using AWS Glue, Spark, PySpark, and Apache Airflow.
Implement and optimize Lakehouse architecture with Apache Iceberg and manage data transformations using Python and dbt.
Ensure application of CI/CD best practices and mentor data engineering team on coding standards and architecture choices.
Strong experience with AWS Glue, Spark, PySpark, Python, and dbt for data transformation and testing.
Experience with Apache Airflow or AWS-native services for workflow orchestration.
Proficiency in Amazon Redshift and SQL performance tuning.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in building and optimizing data pipelines in cloud environments, specifically AWS ecosystem.
Skilled in implementing Lakehouse architectures leveraging Apache Iceberg for efficient data storage and querying.
Able to lead and mentor an engineering team, balancing technical ownership and stakeholder collaboration.