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PwC brand, mid-level Bangalore data engineer role with broad AWS skillset increases applicant competition.
AWS data engineering focus makes technical background important, but skills remain moderately transferable across industries.
Explicit 4-8 years requirement plus mandatory AWS data stack and technical skills implies strict filtering.
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Design, develop, and maintain ETL/ELT data pipelines using AWS services including Glue, Lambda, Step Functions, and EMR.
Build and optimize data lakes and data warehouses leveraging Amazon S3, Redshift, Athena, and Snowflake.
Ensure data quality, integrity, and security using AWS Lake Formation, IAM, and KMS, supporting enterprise data governance and analytics initiatives.
4-8 years of relevant experience in data engineering or analytics.
Strong proficiency in SQL, Python, and PySpark mandatory.
Expertise with AWS data ecosystem: Glue, Redshift, S3, Lambda, EMR, Athena is required.
Educational qualification: B.Tech / M.Tech / MBA / MCA.
Experienced working with enterprise data governance and data management frameworks in advisory or professional services environment.
Demonstrates deep technical expertise in AWS data services with a focus on building scalable, secure data architectures.
Preferably certified with AWS Data Analytics – Specialty or AWS Certified Solutions Architect to signal advanced AWS competency.