Development of micro services and APIs according to the functional domain and design.

Integration of the micro services with the front end code.

Enhancements and fixing bugs in existing code

Following code quality standards according to sonar quality checks

Implement version control mechanism using GIT

Code reviews and peer reviews

Implement Junit test cases for all the APIs built

Review of the test cases to ensure that Unit Test Plan covers all conditions provided in program specifications.

Perform integration testing to ensure that integrated modules are working correctly after deployed to environment

Working knowledge of database, ability to write basic sql/nosql queries.

Experience in writing automation scripts using Java, TestNG, Selenium

Strong analytical and troubleshooting skills, including requirements analysis and basic application knowledge.

Familiarity with entire software development life cycle and test cycles (Unit, Regression, Functional, Systems, Performance and Volume, User Acceptance).

Detailed and effective written communication skills for documenting the features tested and bugs found.

Highly organized, detail oriented, extremely responsive and able to prioritize multiple tasks.

Self-motivated, works well independently and with others.

Extensive experience as a Data Engineer with strong proficiency in Python and Cloud Technologies (AWS preferred).

Proficient in Automating ETL processes and AWS Data/Infrastructure management using Python.

Strong hands-on experience with AWS services like S3, Athena, EMR, Glue, Redshift, Kinesis, and SageMaker.

Experience with SQL/Unix/Linux scripting for data workflows.

Development and testing experience with Cloud/On-Prem ETL Technologies (Ab Initio, AWS Glue, Informatica, Alteryx).

Experience in data migration from On-Prem to Cloud (preferred).

Skilled in DevOps/Data Ops practices, specifically in large-scale application testing.

Familiarity with Data Science platforms such as Sage Maker, Machine Learning Studio, or H2O.