Quality Assurance Engineer

About the Role

We are looking for a QA Engineer to ensure the reliability, accuracy, and performance of our data and AI-driven platform. You will design and execute test plans, build automation frameworks, and validate large-scale data workflows, APIs, and user experiences.

This role is ideal for someone with strong analytical skills, a data-driven mindset, and a passion for building automated, high-quality validation pipelines for complex systems.

Key Responsibilities

Test Strategy & Planning

- Develop and maintain comprehensive test plans for backend, frontend, and integration layers.
- Define test coverage across functional, regression, performance, and data validation areas.
- Collaborate with product managers and engineers to define acceptance criteria and quality goals.

Automation & Framework Development

- Design and implement test automation for APIs, UIs, and data pipelines using modern tools.
- Integrate test automation into CI/CD workflows to support continuous delivery.
- Build reusable libraries for common validation routines such as schema checks, API response validation, and data consistency testing.

Functional & Integration Testing

- Validate data flow, transformations, and system integrations across multiple services.
- Test API endpoints, message queues, and user interfaces for reliability and correctness.
- Conduct end-to-end scenario testing across multiple environments and configurations.

Performance & Reliability Testing

- Execute load and stress testing to identify bottlenecks and scalability issues.
- Monitor and analyze performance metrics to ensure system stability under different workloads.
- Collaborate with Dev Ops and SRE teams to improve system resilience and observability.

Data Validation & Quality Assurance

- Verify data accuracy, completeness, and consistency across datasets and storage systems.
- Test data ingestion, transformation, and lineage tracking for correctness.
- Develop automated validation for metadata, schema evolution, and compliance requirements.

Collaboration

- Work closely with developers, data engineers, and operations teams to reproduce and resolve issues.
- Participate in design and code reviews from a quality perspective.
- Contribute to process improvement and quality best practices within the engineering team.

Required Skills

Core Skills

- Strong experience in test automation using Python, JavaScript, or Java.
- Hands-on with frameworks like PyTest, Playwright, Cypress, or Robot Framework.

- Experience with API testing (Postman, REST Assured, Newman) and CI/CD pipelines (Git Hub Actions, Jenkins, Git Lab).
- Solid understanding of software testing methodologies — functional, integration, regression, and performance.

Data & Systems Knowledge

- Working knowledge of SQL and data validation principles.
- Familiarity with data pipelines, ETL workflows, and modern data platforms (Snowflake, Big Query, Databricks, etc.).

- Experience with cloud environments (AWS, GCP, or Azure).
- Exposure to observability and monitoring tools (Prometheus, Grafana, or similar).

Nice to Have

- Experience testing microservices or Kubernetes-based architectures.
- Familiarity with data governance or compliance automation.
- Understanding of performance testing tools (JMeter, Locust, k6).
- Exposure to LLM- or AI-powered applications.

Education

- Bachelor’s degree in Computer Science, Information Systems, or equivalent experience.

What We Offer

- Work on next-generation data and AI systems that impact enterprise-scale users.
- Collaborative environment with autonomy and ownership.
- Competitive compensation, benefits, and career growth opportunities.
- Flexible remote or hybrid work setup.