ETL Tester Responsibilities:
Realising and evaluating the business requirements and data mapping documentation on creating and designing test plans/strategies is equally important.

Prepare and design complete test strategies, test scenarios, and test requirements depending on the ETL process.

Create transformation test data sets and ETL process validation tools to apply.

Execut certain test cases to verify data transformation and load the data on target system.

Along with other tests, such performance testing, do data sanity checks, validity, and reliability tests.

Validation and Verification of Data:

As you load, change, and move the data to ensure integrity has been preserved.

Make sure data transformations are carried out for data manipulation as advised by the company policies.
As per the defect management life cycle, develop, document, and track flaws.

Report flaws to clarify and help the development team to solve problems.

Perform performance testing to find less effective areas and the extent to which one may scale the current ETL systems.

Make sure that the identification of regions with inadequate data flow is done properly to address the reasons behind delayed traffic.

Handle regression testing such that, following integration of new changes, the current ETL systems remain valid.

Verify that formerly tested functionalities remain stable so as to avoid any problems resulting from this.
Create and maintain automated test cases for long, drawn-out and regular routine tests.

Choose ETL testing tools and frameworks to create script-based testing to validate and verify data.

Record-keeping and Reporting:

Record in great detail test strategies, test cases, test outcomes, defect reports.
Make sure the stakeholders have timely and recorded knowledge of the testing operations and findings.

Needed Competencies for an ETL Tester:

Technical prowess:

knowledge of more sophisticated SQL features as well as database querying and data verification applications of it.

Experience utilising Informatica, Talend, Apache Nifi, SSIS, and other comparable ETL tools.

Previous knowledge of the ideas of data warehousing and their design.

The knowledge or coding skills in a programming language like Java or Python about the automation of tasks.

analytical and problem-solving ability:

Capacity to solve problems helps one understand company norms and data assessment.

Possible to identify, examine, and resolve the troublesome problems with the data set and quality.

Considerate Details:

rather painstaking in one’s efforts to improve the validity of the gathered data.
Possibility to perform high precision data verification at every ETL process stage.

Understanding of Business Processes:

Broad awareness of corporate domains and application of data inside the particular company adaptability in converting customer needs into testing criteria and standards.

Skills of Communication:

Particularly in written and spoken forms, good communication skills will enable one to engage with other stakeholders as well as project team members.
The general results and the documentation and reporting of testing activities are somewhat flexible.

Experience with instruments for testing:

Prior knowledge with data profiling and data quality tools such Apache gill, Talend data quality, or informatics data quality; knowledge with test management and defect tracking platforms including Rigour and Immediate, JIRA, HP ALM, or TestRail.

Flexibility of using new tools and techniques in respect of ETL and Data warehousing perspective reflects constant learning.

Following the lifetime learning policy and staying current with field standards and advances can help you.

Learn More:

https://www.geeksforgeeks.org/what-is-etl-testing/