Techstra Solutions

QA Practice Leader

Techstra Solutions

full-time

Posted on:

Origin:  • 🇺🇸 United States • Pennsylvania

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Job 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).