QA Engineer

QA Engineer – Web, API & Data Engineering (Spark/Scala + Databricks)

About the Role: We are seeking a QA Engineer who can validate complex end‑to‑end business flows across a multi‑layer architecture, including React UI, Java/Spring Boot APIs, Databricks Spark/Scala pipelines, MySQL, and Elasticsearch. The QA is responsible for testing business requirements and acceptance criteria, preparing smoke and regression test suites, and ensuring formal quality sign‑off.

Business Requirements & Acceptance Criteria Validation:

• Analyze business requirements and user stories to extract testable acceptance criteria.

• Create a Requirements Traceability Matrix (RTM) mapping requirements to test cases.

• Validate each acceptance criterion through end‑to‑end scenario execution.

• Document expected vs actual results with evidence.

• Drive QA sign‑off with complete coverage reports. Web Application Testing

• Test React UI for correctness, layout, responsiveness, and edge cases.

• Validate backend APIs.

• Perform functional, integration, regression, and end‑to‑end testing across UI API DB ES flows. Spark/Scala & Databricks Pipeline Testing

• Validate Spark/Scala ETL transformations, joins, aggregations, and business rules.

• Validate Delta Lake behavior across Bronze/Silver/Gold layers.

• Check job dependencies, orchestration, schema evolution, and partition logic. Database Testing (MySQL)

• Write SQL queries for data validation, integrity checks, transformations, and derived fields.

• Validate Databricks‑loaded MySQL tables. Elasticsearch Testing

• Validate index mappings, analyzers, document counts, and search accuracy.

• Confirm MySQL ES synchronization. Azure Cloud Validation

• Validate deployments on Azure App Services, Functions, Storage, and Key Vault.

• Verify logs, configuration, telemetry, and environment settings. Test Strategy, Suites & Documentation

• Create and maintain smoke test suites for critical path validation.

• Develop regression suites covering all functional areas.

• Maintain RTM, end‑to‑end flow documentation, test plans, and evidence.

• Log defects with clear reproduction steps and supporting data.
  

Required Qualifications:

• 4–7 years of QA experience across web, API, and data engineering layers.

• Strong UI, API, and data validation skills.

• Experience validating Databricks Spark/Scala pipelines and Delta Lake.

• Experience validating Elasticsearch indices and search behavior. Preferred Skills

• Automation experience with Playwright/Cypress/Selenium or REST Assured/Karate.

• Python or PySpark for large‑scale data validation.

• Familiarity with Azure DevOps/GitHub Actions CI/CD validation.
  

Soft Skills:

• Strong analytical and documentation skills.

• Ability to work with cross‑functional teams.

• High ownership and attention to detail.