QA Engineer - Big Data Products

Location: Remote (India, IST)

Duration: 2-Year Contract

Role Overview:

We are seeking a Senior QA Engineer/SQA Analyst to support large-scale Big Data product development in highly data-sensitive environments. This role involves validating complex data flows, ensuring quality across terabyte-scale datasets, and collaborating with global stakeholders to deliver secure, reliable, and high-performing data platforms.

Key Responsibilities:

- Design and execute test plans, scenarios, and data validation frameworks for Big Data applications.

- Perform manual and automated testing at the application and API level.

- Validate large datasets, ETL jobs, and complex data pipelines.

- Document and track defects, collaborating with developers for resolution.

- Partner with Product Owners and engineering teams to align QA priorities with business objectives.

- Contribute to release readiness and compliance with organizational quality standards.

Required Skills & Experience:

- Big Data background: Testing data-intensive products, analytics platforms, or large-scale data environments.

- Strong manual testing expertise with detailed scenario design.

- Proficiency in SQL for data validation and troubleshooting.

- Hands-on experience with automation frameworks (Selenium, Protractor, TestComplete, BDD with Cucumber/Gherkin).

- Familiarity with API testing tools (JMeter, Rest Assured, ReadyAPI, SoapUI).

- Proficiency in Java and/or Python for automation scripting.

- Knowledge of QA processes, defect tracking (JIRA), and release management.

- Excellent communication and collaboration skills in distributed teams.

Ideal Candidate Profile:

- Senior-level QA professional with notable client/project experience in Big Data environments.

- Comfortable working with on-premises data platforms (non-cloud) due to client sensitivity.

- Proven ability to manage multiple priorities while maintaining high quality standards.

- Strong analytical mindset, attention to detail, and ability to work independently or in global teams.