Senior QA Engineer​/SDET

Senior-Level QA Engineer / SDET

An accomplished Senior-level QA Engineer / SDET with 10–15+ years of experience specializing in test automation, data validation, backend/API testing, ETL QA, and enterprise-grade CI/CD quality engineering. Highly effective in building automation frameworks, validating complex data systems, ensuring data integrity, supporting rapid release cycles, and driving quality excellence across engineering teams. Demonstrates deep experience across healthcare, cloud, analytics, and large-scale distributed systems domains.

Known for mentorship, proactive problem solving, and a strong shift-left mindset that elevates product reliability and delivery confidence. Actively collaborates and seeks Engineering Lead and Architect direction setting the tone for their engineering peers.

• Test Automation & Framework Development
• Designs and builds scalable automation frameworks for API testing, backend & distributed systems validation.
• Builds automation using Python, Java
• Creates highly parallel, stable, and reusable testing infrastructure.
• Validates large-scale ETL workflows, transformation logic, and end-to-end data flows.
• Designs automated data validation suites using Python/PyTest.
• Experienced with SQL, No
  
  SQL, Snowflake, Airflow, Kafka, AWS
• Automates and validates RESTful APIs using Postman, Swagger, SoapUI, Karate DSL, Robot Framework.
• Extensive API automation across enterprise environments.
• Hands-on experience across AWS CI/CD systems.
• Develops cloud-native test infrastructure.

Education/

Experience:

A Bachelor's degree in a quantitative or business field (e.g., statistics, mathematics, engineering, computer science).

Requires 2 – 4 years of related experience.

Or equivalent experience acquired through accomplishments of applicable knowledge, duties, scope and skill reflective of the level of this position.

Technical

Skills:

• One or more of the following skills are desired.
• Experience with Claims/Healthcare;
  Big Data;
  Data Processing
• Experience with Other: diagnosing system issues, engaging in data validation, and providing quality assurance testing
• Experience with Data Manipulation;
  Data Mining

Experience with Other:

• Experience working in a production cloud infrastructure
• Experience with one or more of the following:
• Data Engineering/ETL
• Generative AI Tools
• Programming
  
  Languages:
  
  Python/Java/Unix Shell Scripting/Oracle SQL/PLSQL/ETL/Control-M/MFT
• Cloud & Infra Platforms:
  Cloud Kubernetes, AWS, Docker, Rancher, Jenkins
• Automation Tools:
  Cypress, Playwright, PyTest.
• Databases:
  MongoDB, Oracle/SQL, SQL Server, SQL Lite, MySQL, MongoDB, Snowflake
• Containerization:
  Docker, Kubernetes
• Development Tools:
  Jira, Confluence, Git, Juypter Hub, Databricks.