Walk In || AWS Data Engineer+Pyspark
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Role- Walk In || AWS Data Engineer + Pyspark Experience: 5 - 12 Years
Walk In Venue:
Tata Consultancy Services A Block,2nd floor ,Yeshwanthpur Towers 2GGW+54C, Yeshwanthpur Industrial Suburb, Sattva Knowledge Point Mahalakshmi Layout, Bengaluru,
Walk In Date - 29-August-26 (Saturday)
Role Summary
We are seeking an experienced AWS Data Engineer+ Databricks+ Pyspark to design, build, and optimize scalable data pipelines and analytics solutions on AWS. The ideal candidate has strong expertise in cloud-native data services, big data processing, and end‑to‑end data engineering practices.
Required Skills & Qualifications
Strong experience with AWS services used for data engineering (Glue, S3, Lambda, EMR, Redshift, Athena, Databricks, Kinesis). Proficiency in Python and SQL. Hands-on experience with distributed data processing frameworks (Spark, PySpark, Hadoop). Experience building data lakes, data warehouses, and lakehouse architectures. Strong understanding of ETL/ELT design patterns and data modeling (Star/Snowflake). Knowledge of CI/CD, infrastructure-as-code (Terraform/CloudFormation), and Git. Familiarity with data governance, security, and compliance frameworks
Role- Walk In || AWS Data Engineer + Pyspark Experience: 5 - 12 Years
Walk In Venue:
Tata Consultancy Services A Block,2nd floor ,Yeshwanthpur Towers 2GGW+54C, Yeshwanthpur Industrial Suburb, Sattva Knowledge Point Mahalakshmi Layout, Bengaluru,
Walk In Date - 29-August-26 (Saturday)
Role Summary
We are seeking an experienced AWS Data Engineer+ Databricks+ Pyspark to design, build, and optimize scalable data pipelines and analytics solutions on AWS. The ideal candidate has strong expertise in cloud-native data services, big data processing, and end‑to‑end data engineering practices.
Required Skills & Qualifications
Strong experience with AWS services used for data engineering (Glue, S3, Lambda, EMR, Redshift, Athena, Databricks, Kinesis). Proficiency in Python and SQL. Hands-on experience with distributed data processing frameworks (Spark, PySpark, Hadoop). Experience building data lakes, data warehouses, and lakehouse architectures. Strong understanding of ETL/ELT design patterns and data modeling (Star/Snowflake). Knowledge of CI/CD, infrastructure-as-code (Terraform/CloudFormation), and Git. Familiarity with data governance, security, and compliance frameworks