Execute data quality and testing initiatives for a data platform, including ETL testing, data validation, load and performance testing, automated regression testing, AWS pipeline monitoring, and Power BI report validation. Develop test cases, verify ingestion and transformation logic, investigate data anomalies, document results, and collaborate with engineers, analysts, and stakeholders to maintain data integrity, availability, and reliability.
Overview
Duties & Responsibilities
symplr is seeking a highly skilled and motivated Senior Data Quality Engineer with 5+ years of experience to execute testing initiatives for our robust Data Platform. This role is instrumental in maintaining the integrity, reliability, and performance of our data systems. The ideal candidate will bring strong expertise in ETL testing, data validation, AWS-based data workflows, and Power BI reports, with a solid foundation in Test Automation and scripting. Readiness on learning/understanding new tools.
Duties & Responsibilities
- Contribute to the development and execution of data quality strategies and best practices to support the organization’s data initiatives.
- Web UI/tools testing: Create testcases and scenarios based on features and requirements.
- Load Testing: Ability to test the system with high volume of data
- ETL Testing: Design and perform thorough ETL tests, including test case development, data validation, transformation accuracy, end-to-end pipeline testing, and performance testing.
- AWS Data Pipeline Monitoring: Support the monitoring of AWS-based pipelines using services like S3, SQS, Lambda etc. to ensure workflows, data accuracy, completeness, and reliability.
- Power BI Reports: Ensure data accuracy and consistency in Power BI reports by validating data lineage, transformation logic, and report outputs against source systems.
- Collaboration: Work alongside data engineers, analysts, and business stakeholders to understand data flows and resolve data quality issues.
- Documentation: Maintain clear and detailed documentation of testing procedures, test results, and quality metrics in addition to product/processes workflows.
- 5+ years of experience in data quality engineering, data testing, or related fields.
- Strong hands-on experience with ETL testing and data validation techniques.
- Experience working with AWS data services, including Glue, S3, Athena, MSK, SQS, Lambda, Step Functions, etc.
- Experience in building Automated regression test suites
- Proficiency in writing SQL and basics of any OOP languages
- Experience validating data using Power BI reports, including understanding of data models and report logic.
- Familiarity with test management tools such as Azure DevOps, Zephyr, or equivalent.
- Validated ingestion and transformation logic for large-scale batch and real-time data workflows.
- Experience working in Agile environments (Scrum/Kanban).
- Exposure to data governance principles or data observability tools is a plus.
- Strong problem-solving skills and a proactive approach to identifying data quality issues.
- Ensured data availability and integrity for analytics & reporting teams.
- Good communication skills and the ability to work effectively with cross-functional teams.
- Continuous learning mindset and willingness to adapt to new technologies and techniques.
Good to have:
- Automation & Scripting: Develop Python-based scripts to automate data quality checks and validation processes.
- Experience in Conducting root-cause analysis for data anomalies, improving issue resolution time.
- Understanding of Data warehouse tools like Redshift
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