Qa Engineer

Bridgenext; United States; Remote; USD 90,000 - 120,000; Full time

Job summary

Bridgenext is seeking a detail-oriented Data QA Engineer to validate data platforms, analytics solutions, and reporting systems. You will apply QA methodologies, perform data validation, and write SQL queries to ensure data accuracy and reliability.

Exposure to BI testing, Databricks, and Microsoft Fabric is highly desirable, as is experience with API testing using Postman. Strong communication and collaboration skills will help you partner with data engineers and product teams.

Qualifications

• 3+ years in Quality Assurance, Data Testing, or Software Testing.
• Strong SQL skills with data validation checks.
• Manual testing of data-intensive applications.
• Basic API testing with Postman.
• Excellent written and verbal communication.

Skills

SQL data validation

API testing

QA methodologies

SDLC/STLC

Data testing

Collaboration

Test documentation

Tools

Databricks

Microsoft Fabric

Postman

Job description

We are seeking a detail-oriented Data QA Engineer to support the validation and quality assurance of data platforms, analytics solutions, and reporting systems. The ideal candidate will have strong fundamentals in testing, data validation, SQL querying, and API testing, with an interest in working with modern data ecosystems. Exposure to BI testing, Databricks, and Microsoft Fabric is highly desirable.

Required Skills & Qualifications

• 3+ years of experience in Quality Assurance, Data Testing, or Software Testing.
• Good understanding of QA methodologies, SDLC, STLC, and defect management processes.
• Strong SQL skills with the ability to write queries involving joins, aggregations, and data validation checks.
• Experience performing manual testing of data-intensive applications or backend systems.
• Basic API testing experience using tools such as Postman.
• Strong analytical, troubleshooting, and problem-solving skills.
• Ability to create clear test documentation, defect reports, and test execution summaries.
• Good communication and collaboration skills.

Good to Have

• Exposure to Business Intelligence (BI) Testing involving reports, dashboards, and analytics validation.
• Familiarity with Databricks and data lakehouse concepts.
• Exposure to Microsoft Fabric, including data pipelines, warehouse, lakehouse, or reporting components.
• Understanding of ETL/ELT testing concepts and data reconciliation techniques.
• Knowledge of cloud data platforms such as Azure Data Services.
• Basic understanding of data warehousing and dimensional modeling concepts.

Professional Skills:

• Solid written, verbal, and presentation communication skills
• Strong team and individual player
• Maintains composure during all types of situations and is collaborative by nature
• High standards of professionalism, consistently producing high quality results
• Self-sufficient, independent requiring very little supervision or intervention
• Demonstrate flexibility and openness to bring creative solutions to address issues