Quality Analyst

Role & Responsibilities:
 

• Conduct UI/platform testing to validate workflows, data‑driven screens, user interactions, and correct rendering of data returned from backend APIs.
• Test backend platform services, event flows, access controls, and error handling behaviours.
• Validate authentication and authorisation boundaries — including role‑based access controls, session behaviour, and expected access restrictions across user types and portals.
• Test file‑based ingestion paths including SFTP uploads — validating file acceptance, rejection handling, schema conformance, and correct downstream processing for both well‑formed and malformed inputs.
• Perform API testing for schema correctness, parameter validation, filtering logic, pagination, and expected outputs.
• Execute automated regression suites, validation scripts, and contribute to extending automation coverage.
• Log defects with clarity, analyse root causes, and collaborate with engineering to drive timely resolution.
• Prepare and maintain test environments, seed representative test data, and support environment promotion readiness.
• Maintain clear test documentation including cases, scenarios, results, and repeatable validation procedures.
• Participate in requirement reviews, refining acceptance criteria and identifying data or testing gaps early in the workflow.
• Assist in validating release readiness through smoke testing, sanity checks, and verification of critical platform features.
• Write SQL queries to set up test data, perform backend assertions, and verify application behaviour against expected results.
• Assist in source‑to‑target reconciliation and data completeness checks — documenting discrepancies, unexpected schema changes, and environment‑specific anomalies for engineering review.
• Grow into pipeline testing — support validation of data transformation outputs and pipeline flow correctness as you build ETL testing skills.
• Support validation of data model correctness, including key constraints, relationship integrity, and query output accuracy.
• Learn to query Snowflake or similar cloud data platforms to validate transformation results and confirm data quality.

Skills & Qualifications:

Must-Have:

• 3–5 years of experience in application‑level functional testing, including frontend workflow validation, API testing, and backend/database testing.
• Hands‑on experience with UI test automation frameworks (e.g. Selenium, Playwright, or Cypress) and API testing tools (e.g. Postman or RestAssured).
• Demonstrated ability to validate end‑to‑end user workflows in web applications, covering form validation, navigation flows, state transitions, and correct rendering of data returned from backend APIs.
• Experience performing API testing (schema validation, parameters, filtering, pagination, response correctness).
• Ability to test backend services, event flows, and error-handling scenarios.
• Experience building or maintaining automated test suites using frameworks such as JUnit, TestNG, pytest, or Cucumber.
• Working knowledge of SQL for data assertions, test data preparation, and result verification.
• Awareness of data sensitivity and PII handling practices — including the importance of using synthetic or anonymised test data and the risks of using production data in non‑production environments.
• Strong analytical and problem‑solving skills with experience performing root cause analysis.
• Ability to work effectively in agile environments with sprints, story refinement, and release cycles.
• Strong communication and documentation skills for reporting defects and test outcomes.

Preferred:

• Familiarity with Azure services relevant to testing — including App Service log streaming, Event Grid / Storage Queue message inspection, Blob Storage file validation, and Azure Monitor / Log Analytics for tracing issues across environments.
• Basic familiarity with containerised deployments — ability to read Docker / container logs and correlate application behaviour with container startup and runtime output.
• Familiarity with Java‑based backend services (Spring Boot) as a context for API test design and log interpretation.
• Exposure to ETL or data pipeline concepts and basic pipeline validation techniques.
• Awareness of cloud data platforms such as Snowflake and the ability to run basic SQL queries against them.
• Familiarity with transformation tools such as dbt or similar; prior hands‑on use is a strong plus.
• Basic un