QA Manual - Senior Engineer @ Iris Software

Manual Testing, Data Testing, ETL Testing, API Testing, SQL, Test Case Design, STLC, Jira, Cloud Concepts (AWS)

Good to Have:

Cucumber BDD, DBT testing exposure, Databricks SQL/PySpark understanding, BI Testing (Sigma/Tableau/Power BI)

Responsibilities

Data & Platform Testing

• Analyze user stories, data models, DBT transformation logic, and mapping documents to build comprehensive data test cases.
• Execute end-to-end ETL/Data pipeline testing across multiple layersraw, staging, curated, and analytics layers.
• Validate data transformations implemented in DBT models, ensuring correctness of joins, aggregations, schemas, and business rules.
• Perform detailed data validation using SQL , SQL Server, and Databricks environments.
• Test data ingestion workflows built on AWS services such as S3, Glue, Lambda, Step Functions, etc.
• Conduct API testing for data ingestion, extraction, and system integrations.
• Validate BI dashboards and metrics on Sigma, ensuring accuracy, filters, and data freshness.

Functional & Web Testing

• Test web-based components (if any) that interact with the data platform such as admin portals, configuration panels, or data access layers.

Defect Management & Collaboration

• Identify, reproduce, and document defects using Jira, ensuring proper data-level evidence.
• Collaborate closely with Data Engineers, DBT developers, and Cloud teams to understand transformations, data flows, and architecture impacts.
• Participate actively in Agile ceremoniesstand-ups, grooming, sprint planning, retrospectives.

Quality Process & Contribution

• Contribute to data quality processesvalidation rules, sampling methodologies, reconciliation checks, regression strategies.
• Continuously improve test artifacts, test data, and quality coverage.
• Stay current with modern data engineering and cloud testing practices.

Skills

• Strong SQL skills with ability to write complex joins, aggregations, window functions, and data comparisons.
• Experience testing data warehouses or data lakes using or Databricks.
• Understanding of DBT (models, seeds, snapshots, lineage).
• Exposure to AWS services relevant to data workflows.
• Experience in API testing (Postman, Swagger, REST/JSON validation).
• Familiarity with Gherkin and BDD-style test documentation.
• Test management experience using Zephyr, Jira.
• Strong experience in creating test plans, test scenarios, regression packs.
• Excellent communication and coordination skills.