QA Data Engineer

INVID•San Juan, PR

13d•Hybrid

About The Position

We are seeking a detail-oriented and analytical QA Data Engineer to ensure the accuracy, reliability, and quality of our data platform and reporting solutions. This role plays a critical part in validating data pipelines, transformations, and BI outputs, supporting key goals around data accuracy, auditability, and release quality. The ideal candidate brings strong experience in data testing, reconciliation, and BI validation, with the ability to define testing strategies and ensure high-quality releases across the data lifecycle—from ingestion to reporting. What sets INVID apart is our collaborative and flexible work environment. We encourage our team to raise the bar in everything they do while maintaining a healthy work-life balance. With our hybrid work model, team members thrive both in the office and remotely. We foster a culture of mutual respect, autonomy, and accountability, where your voice matters and your growth is supported. From structured career paths and paid professional development to access to industry events, we’re committed to your success.

Requirements

5–7 years of experience in QA, data engineering, BI testing, or related roles
Proven experience testing ETL/ELT pipelines and BI/reporting solutions
Strong skills in data validation, reconciliation, and root cause analysis
Experience validating Power BI reports and dashboards, including UAT coordination
Familiarity with software/data release cycles (Dev/Test/Prod) and quality assurance best practices
Ability to work independently, define testing approaches, and manage end-to-end QA processes
Strong attention to detail with excellent documentation and communication skills
Ability to obtain security clearance (if required)
US Resident | US Citizenship
Fully Bilingual (Spanish and English)

Nice To Haves

Experience with automated testing approaches for data validation and regression testing
Working knowledge of Python or scripting for automating data comparison and validation tasks
Familiarity with modern data platforms (e.g., Microsoft Fabric, Azure data ecosystem)
Understanding of data lineage, governance, and auditability concepts
Experience working in cross-functional teams within data transformation initiatives

Responsibilities

Define and execute test strategies and test plans across data ingestion, transformation, and reporting layers, including UAT
Validate data accuracy through end-to-end reconciliation (source vs. transformed vs. report-level outputs)
Perform Power BI validation and testing in non-production environments prior to release
Develop and maintain regression testing frameworks to support ongoing data and reporting changes
Document defects, test results, and release readiness criteria, ensuring clear audit trails
Collaborate with data engineers, BI developers, and business stakeholders to ensure high-quality data deliverables
Support Dev/Test/Prod release validation processes and continuous improvement of QA practices
Work under Agile methodologies and frameworks such as Scrum or Kanban.
Provide daily status and feedback on the work performed.
Assist in the analysis, design, development, and deployment of necessary data.
Provide accurate explanations of any written code.
Communicate with internal and external personnel in English or Spanish to discuss requirements and specifications, provide status updates, and explain the work performed.