QA Analyst
AIQ
CypressSelenium
QA Practice Leader
Techstra Solutions
full-time
Posted on:
Location: Pennsylvania • 🇺🇸 United States
Visit company websiteJob Level
Senior
Tech Stack
Amazon RedshiftApacheAWSAzureCloudETLGoogle Cloud PlatformHadoopInformaticaPythonSeleniumSparkSQLTableau
About the role
- Design, develop, and execute test strategies and plans for data-related projects (ETL, data lakes, data warehouses, SPARK).
- Validate data integrity, transformations, and business logic from source to target systems.
- Perform advanced SQL queries to verify large data sets and identify anomalies or inconsistencies.
- Automate data validation processes using appropriate tools and scripting languages (e.g., Python, SQL, Shell).
- Collaborate with cross-functional teams (developers, BAs, DBAs, data engineers) to understand data flow and requirements.
- Validate regulatory and compliance-related reports (e.g., AML, KYC, Basel, CCAR, etc.).
- Participate in Agile ceremonies (stand-ups, sprint planning, retrospectives).
- Investigate and document data defects and work with teams to ensure timely resolution.
- Create and maintain detailed test documentation, test cases, and test results for audit and compliance purposes.
Requirements
- Bachelor’s degree in Computer Science, Information Systems, or a related field.
- 7+ years of QA experience, with a focus on data testing, ETL validation, and database QA.
- Strong knowledge of SQL (joins, CTEs, window functions, aggregations).
- Experience testing data in data warehouses (e.g., Snowflake, Redshift, Teradata) and ETL tools (e.g., Informatica, Talend, Apache NiFi).
- Hands-on experience with banking or financial domain data, including compliance and risk reporting.
- Familiarity with data quality frameworks, data governance, and metadata management.
- Knowledge of testing tools and frameworks (e.g., Selenium, PyTest, JIRA, TestRail).
- Experience working in Agile/Scrum environments.
- Excellent analytical, communication, and problem-solving skills.
- Preferred: Experience with Big Data platforms (e.g., Hadoop, Spark).
- Preferred: Knowledge of cloud data services (AWS, Azure, GCP).
- Preferred: Familiarity with data visualization tools like Tableau or Power BI.
- Preferred: Financial certifications (e.g., CFA, FRM) or QA certifications (e.g., ISTQB).
