As a Quality Analyst you will be involved in every phase of SDLC and focus on Functional
testability Automation and Performance of the software.
Responsibilities:
- Selecting and integrating Data tools and frameworks required to provide requested capabilities.
- Technical guidance for software engineers engaged in the design coding reviewing and testing of enterprise software
- Collaborate with Data Scientists Data Engineers and Software Engineers to understand data and models to develop QA tests to validate.
- Implementing ETL process
- Monitoring performance and advising any necessary infrastructure changes
- Defining data retention policies
- Collaborate with the Recruitment team for Hiring
Requirements
Requirements:
1. Experience creating detailed and comprehensive test suites using programming languages
such as Python
2. Experience writing complex SQL queries to extract or validate data
3. Good understanding of Big Data concepts and NoSQL DB preferable
4. Proficient in writing Hive QL and Spark QL queries
5. Should have handson experience in Data testing tools like DBT iCEDQ QuerySurge
Denodo informatica etc.
6. Good Understanding on QE Testing types for testing Data quality.
7. Troubleshooting the application and rectifying the problem in an earlier stage. Involved in
defect life cycle management.
8. Ability to test software & get UAT done from business users in Agile manner
9. Continuous automation to increase test coverage and efficiency
10. Proactive & reactive support in deployments & production environment
11. Hands on experience in Linux or Unix
12. Good debugging skills
13. Ability to solve any ongoing issues with operating the cluster
14. Experience with integration of data from multiple data sources
15. Experience with BI tools like PowerBI and Tableau is a plus
16. Experience with various messaging systems such as Kafka or RabbitMQ
17. Strong analytical and excellent communication skills.
Requirements: 1. Experience creating detailed and comprehensive test suites using programming languages such as Python 2. Experience writing complex SQL queries to extract or validate data 3. Good understanding of Big Data concepts and NoSQL DB preferable, 4. Proficient in writing Hive QL and Spark QL queries 5. Should have hands-on experience in Data testing tools like DBT, iCEDQ, QuerySurge, Denodo, informatica etc. 6. Good Understanding on QE Testing types for testing Data quality. 7. Troubleshooting the application and rectifying the problem in an earlier stage. Involved in defect life cycle management. 8. Ability to test software & get UAT done from business users in Agile manner 9. Continuous automation to increase test coverage and efficiency 10. Proactive & reactive support in deployments & production environment 11. Hands on experience in Linux or Unix 12. Good debugging skills 13. Ability to solve any ongoing issues with operating the cluster 14. Experience with integration of data from multiple data sources 15. Experience with BI tools like PowerBI and Tableau is a plus 16. Experience with various messaging systems, such as Kafka or RabbitMQ 17. Strong analytical and excellent communication skills.