Vadodara, Gujarat, India
Information Technology
Full-Time
Virtusa
Overview
AWS Data Engineer
WorkMode :Hybrid
Work Location : Chennai / Hyderabad / Bangalore / Pune / mumbai / gurgaon
Work Timing : 2 PM to 11 PM
Primary : Data Engineer
AWS Data Engineer - AWS Glue, Amazon Redshift, S3
ETL Process , SQl, Databricks
JD
Examining the business needs to determine the testing technique by automation testing.
Maintenance of present regression suites and test scripts is an important responsibility of the tester.
The testers must attend agile meetings for backlog refinement, sprint planning, and daily scrum meetings.
Testers to execute regression suites for better results.
Must provide results to developers, project managers, stakeholders, and manual testers.
Responsibility
AWS Data Engineer
Design and build scalable data pipelines using AWS services like AWS Glue, Amazon Redshift, and S3.
Develop efficient ETL processes for data extraction, transformation, and loading into data warehouses and lakes.
Create and manage applications using Python, SQL, Databricks, and various AWS technologies.
Automate repetitive tasks and build reusable frameworks to improve efficiency.
WorkMode :Hybrid
Work Location : Chennai / Hyderabad / Bangalore / Pune / mumbai / gurgaon
Work Timing : 2 PM to 11 PM
Primary : Data Engineer
AWS Data Engineer - AWS Glue, Amazon Redshift, S3
ETL Process , SQl, Databricks
JD
Examining the business needs to determine the testing technique by automation testing.
Maintenance of present regression suites and test scripts is an important responsibility of the tester.
The testers must attend agile meetings for backlog refinement, sprint planning, and daily scrum meetings.
Testers to execute regression suites for better results.
Must provide results to developers, project managers, stakeholders, and manual testers.
Responsibility
AWS Data Engineer
Design and build scalable data pipelines using AWS services like AWS Glue, Amazon Redshift, and S3.
Develop efficient ETL processes for data extraction, transformation, and loading into data warehouses and lakes.
Create and manage applications using Python, SQL, Databricks, and various AWS technologies.
Automate repetitive tasks and build reusable frameworks to improve efficiency.
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