About the Role
The role involves designing and implementing automated testing solutions focused on data integrity, pipeline validation, and system reliability within a mortgage technology environment. Candidates will work closely with engineering and data teams to improve test coverage and ensure robust data workflows.
Responsibilities
- Develop and maintain automated test frameworks for data pipelines and ETL processes
- Design test strategies that validate data accuracy, consistency, and transformation logic
- Collaborate with data engineers and backend developers to identify testable requirements
- Implement end-to-end testing for data-intensive applications
- Monitor data quality metrics and report anomalies
- Create synthetic datasets to support testing scenarios
- Integrate testing workflows into CI/CD pipelines
- Troubleshoot and debug data-related defects across environments
- Ensure compliance with data governance and regulatory standards
- Optimize test execution performance and resource usage
- Document test cases, results, and data validation procedures
- Support production data incident investigations
- Evaluate new testing tools and frameworks for data validation
- Mentor junior team members in test automation best practices
- Participate in code and test plan reviews
- Maintain version control for test scripts and configurations
- Work with large-scale datasets across cloud environments
- Validate schema changes and data model updates
- Assess impact of system changes on existing data workflows
- Contribute to reliability and performance testing efforts
Compensation
Competitive salary and benefits package
Work Arrangement
Remote
Team
Distributed team with members across Latin America
Why This Role Matters
The platform handles sensitive financial data, making data accuracy and system reliability critical. This role directly impacts the trustworthiness of lending decisions and customer outcomes by ensuring data integrity across systems.
Technology Stack
The system uses Python, SQL, Apache Airflow, AWS services, Docker, and Kafka. Testing tools include PyTest, Great Expectations, and custom validation scripts integrated into CI pipelines.
Not available
