SDET

Title: SDET Location: Dallas (TX) or Tampa (FL) Duration: 6 months (possibility of extension)
JD:

Overview:
We are seeking a highly skilled and motivated Software Development Engineer in Test (SDET) to join our Data Services team. This role is critical to ensure the quality and reliability of complex data products by designing and implementing a robust Python-based testing framework. The ideal candidate will bring deep expertise in ETL testing, Python, and SQL, with optional experience in Java to support integration with existing test frameworks.

Key Responsibilities:

• Design and develop a scalable Python-based test automation framework for validating data pipelines and reports.
• Collaborate closely with data engineers, product owners, and QA teams to define effective test strategies and ensure comprehensive coverage.
• Build and maintain test data sets tailored to individual product requirements, and make them available to SDETs for functional testing.
• Develop and maintain automated test scripts for data ingestion, transformation, and output validation.
• Perform in-depth data analysis and validation using SQL across diverse data sources.
• Integrate automated tests into pipelines to enable continuous validation and early defect detection.
• Analyze test results, identify root causes, and work with development teams to drive resolution.
• Optionally support and understand existing Java/Selenium-based test frameworks to ensure compatibility and reuse.

Required Qualifications:

• 5+ years of experience in software testing, with a strong focus on data and ETL pipelines.
• 3+ Years relevant experience in Python + SQL+ETL
• Proven proficiency in Python for test automation and scripting.
• Solid experience with SQL for data validation and analysis.
• Familiarity with version control systems and CI/CD tools.
• Strong analytical thinking, problem-solving abilities, and communication skills.

Preferred Qualifications:

• Experience with Java and Selenium for UI or legacy test framework support.
• Knowledge of cloud data platforms such as Snowflake and AWS.
• Exposure to data governance, data quality, and metadata management tools.