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Tier-1 brand, mid-level generalist data role in Bangalore with broad AWS/Snowflake skill requirements.
Data-engineering skills are broadly transferable across industries, though Snowflake/AWS focus raises domain specificity.
Explicit 4–8 years plus mandatory AWS, Snowflake, Airflow and PySpark requirements increase filtering strictness.
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Design, develop, and maintain scalable AWS-based data pipelines and ETL/ELT workflows using Snowflake, Apache Airflow, Python, PySpark, and AWS services.
Optimize Snowflake data warehousing performance and costs, implement data quality checks, and troubleshoot pipeline and data issues.
Collaborate with data architects, analysts, application teams, and business stakeholders to deliver reliable, scalable data solutions with CI/CD and Agile practices.
4–8 years of hands-on experience in AWS Data Engineering including Snowflake, Apache Airflow, Python, PySpark, and SQL.
Bachelor's or Master’s degree in Computer Science, IT, Engineering, or related discipline (B.Tech/MCA/M.Tech).
Strong skills with AWS services: S3, Glue, Lambda, EMR, Athena, Redshift, IAM.
Experience with ETL/ELT design, data warehousing, dimensional modeling, Git, and CI/CD.
Demonstrated experience in building and optimizing data pipelines on AWS cloud platforms with Snowflake and Apache Airflow.
Proficient in developing complex data transformation and orchestration workflows using Python and PySpark in Agile environments.
Experience collaborating cross-functionally with technical and business teams to translate requirements into scalable data engineering solutions.