Senior Data SDET

Role & responsibilities

• Author and conduct tests for data pipeline requirements and data visualization outputs
• Document data flow, transformations, and quality control processes throughout the data engineering lifecycle
• Generate comprehensive reports on data quality metrics, test results, and anomalies detected
• Communicate data quality issues with the appropriate level of urgency based on business impact
• Write and maintain automated test scripts for data validation, transformation testing, and output verification
• Identify and proactively seek out opportunities to augment data quality frameworks and capabilities
• Collaborate with data engineering, data science, and business stakeholders to drive comprehensive requirements for data pipeline enhancements
• Analyze end user requirements to create and maintain comprehensive test plans for data products
• Execute manual and automated test cases for data pipelines, debug data quality issues, and follow up to ensure resolution
• Identify, reproduce, and report data defects and verify fixes across the data ecosystem
• Participate in agile development process and contribute to continuous improvement of data quality practices
• Represent the data consumers to the data engineers to ensure that requirements are met
• Detect and propose improvements in both the data quality control process and the data engineering lifecycle

Qualifications

• 5+ years testing, building, or supporting data pipelines, data warehouses, or business intelligence solutions
• Experience testing data APIs, ETL processes, and data visualization outputs
• Experience with using ticketing systems such as Jira, aha!, etc.
• Experience with test case management software for data quality initiatives
• Strong analytical skills with the ability to identify patterns in data quality issues
• Experience with SQL, database technologies, and testing concepts
• Knowledge of data validation techniques for both structured and unstructured data
• Excellent written and verbal communication skills. In disagreements, you engage thoughtfully with other perspectives and are willing to compromise
• Demonstrated leadership ability to build, lead and inspire data quality initiatives, foster a positive work culture, and develop talent
• Familiarity with automated testing for data pipelines and data visualization outputs
• Experience with API testing frameworks (Postman, Rest Assured, etc.) for data services
• Experience testing or supporting data warehouses, data lakes, or business intelligence platforms
• Experience writing code using Python, SQL, or other languages common in data engineering
• Desire and ability to take on special engineering initiatives that have an impact on data quality