Software Development Engineer - Test ii

In this vital role you will work closely with data engineers, architects, and product owners to understand the applications being built. The role will be responsible for developing test automation scripts, develop reusable common components for testing, develop load and scalability test scripts, analyze production issues and develop innovative automation for early detection and prevention of those issues, or for self-healing.
Roles & Responsibilities:

• Design, develop, and maintain automated test scripts for data pipelines, ETL jobs, and data integrations.
• Validate data accuracy, completeness, transformations, and integrity across multiple systems.
• Collaborate with data engineers to define test cases and establish data quality metrics.
• Develop reusable test automation frameworks and CI/CD integrations (e.g., Jenkins, GitHub Actions).
• Perform performance and load testing for data systems.
• Maintain test data management and data mocking strategies.
• Identify and track data quality issues, ensuring timely resolution.
• Perform root cause analysis and drive corrective actions.
• Contribute to QA ceremonies (standups, planning, retrospectives) and drive continuous improvement in QA processes and culture.
• Masters degree and 1 to 3 years of computer science and engineering and Test Automation experience OR
• Bachelors degree and 3 to 5 years of computer science and engineering and Test Automation experience OR
• Diploma and 7 to 9 years of computer science and engineering and Test Automation experience

Preferred Qualifications:

Must-Have Skills:

• Experience in QA roles, with strong exposure to data pipeline validation and ETL Testing.

• Domin Knowledge of R&D domain of life science.
• Validate data accuracy, transformations, schema compliance, and completeness across systems using PySpark and SQL.
• Strong hands-on experience with Python, and optionallyPySpark, for developing automated data validation scripts.
• Proven experience invalidating ETL workflows, with a solid understanding ofdata transformation logic,schema comparison, andsource-to-target mapping.
• Experience working withdata integration and processing platformslikeDatabricks/Snowflake,AWS EMR,Redshift etc
• Experience inmanual and automated testingof data pipelines executions for bothbatchandreal-time data pipelines.
• Perform performance testing of large-scale complex data engineering pipelines.
• Ability totroubleshoot data issues independentlyand collaborate with engineering teams forroot cause analysis
• Strong understanding of QA methodologies, test planning, test case design, and defect lifecycle management.
• Hands-on experience with API testing using Postman, pytest, or custom automation scripts
• Experience integrating automated tests intoCI/CD pipelinesusing tools likeJenkins,GitHub Actions, or similar.
• Knowledge of cloud platforms such as AWS, Azure, GCP.

Good-to-Have Skills

• Certifications in Databricks, AWS, Azure, or data QA (e.g., ISTQB).
• Understanding of data privacy, compliance, and governance frameworks.
• Knowledge of UI automated testing frameworks like Selenium, JUnit, TestNG
• Familiarity with monitoring/observability tools such as Datadog, Prometheus, or Cloud Watch

• Excellent analytical and solving skills.
• Strong verbal and written communication skills
• Ability to work effectively with global, virtual teams
• High degree of initiative and self-motivation.
• Ability to manage multiple priorities successfully.
• Team-oriented, with a focus on achieving team goals.
• Ability to learn quickly, be organized and detail oriented.
• Strong presentation and public speaking skills.