As a Data Quality Engineer at PalTech you will play an important role in designing and executing test strategies for end-to-end data validation, ensuring data completeness, accuracy, and integrity across ETL processes, data warehouses, and reports. You will automate data testing using Python, validate fact and dimension tables, large datasets, file ingestions, and data exports while ensuring adherence to data security standards, including encryption and authorization. Proficiency in SQL, Python, ETL/ELT tools, and reporting platforms like Power BI or Tableau is essential. The role requires strong analytical skills, collaboration with cross-functional teams, and the ability to enhance testing processes through automation and best practices.
Roles and Responsibilities
- Create test strategies, test plans, business scenarios, data validation scripts for end-to-end data validation.
- Verify data completeness, accuracy, and integrity throughout the ETL processes and reports.
- Evaluate the performance of ETL jobs and ensure that they meet defined SLAs
- Automate the data testing process using Python or other technologies
- Experienced in validating various types of fact tables and dimension tables
- DWH skills are a must
- Should have expertise in validating larger datasets
- Should have experience working with relational databases
- Should have experience in validation of file ingestions and data exports
- Should be expert in validation of the data security standards implemented in the project
- Should be proficient in SQL, Python, validation of ETL/ELT tools
- Should be proficient in validation of reports and dashboards
- Should be proficient in writing complex scripts to validate business logics and KPIs
- Should be proficient in validating data encryption, anonymization, authorization processes
- Extensive experience in creating test data as and when needed based on the business requirements
- Should be able to identify and validate the corner business use cases
- Prepare comprehensive test documentation including test cases, test results, and test reports.
- Work closely with cross-functional teams including developers, business analysts, and data architects.
- Suggest enhancements and implement the best practices to improve testing processes.
Technical Skills:
- Strong understanding of ETL processes, data warehousing concepts, and SQL.
- Should have strong Python skills
- Experience in ETL testing and reports validation.
- Experience in automation of data validation processes
- Familiarity with ETL tools like ADF, DBT, etc., and defect tracking systems like JIRA.
- Experience with any reporting tools like Power BI, Tableau, etc
Soft Skills:
- Excellent analytical and problem-solving skills.
- Strong communication skills and ability to work in a team-oriented environment.