Data QA Engineer

DarioHealth•New York, NY

14h

About The Position

At Dario, Every Day is a New Opportunity to Make a Difference. We are on a mission to make better health easy. Every day our employees contribute to this mission and help hundreds of thousands of people around the globe improve their health. How cool is that? We are looking for passionate, smart, and collaborative people who have a desire to do something meaningful and impactful in their career. The primary responsibilities of this job include:

Requirements

Bachelor's degree in computer science, Engineering, or a related field.
6+ years of experience in QA, test automation, or data quality roles.
Strong proficiency in programming and query languages.
Proven experience testing ETL/ELT processes and data warehouse platforms.
Familiarity with data pipeline tools and orchestration systems.
Experience handling or working around PHI/PII data with a strong understanding of compliance requirements(HIPAA or similar).
Strong understanding of QA methodologies (STP/STD/STR).
Hands-on experience with AI/ML-based test automation tools and frameworks, including validation of LLM-driven applications.
Strong expertise in AI-assisted test case generation, self-healing locators, and intelligent defect detection.
Experience with version control systems and CI/CD processes.
Business-minded with the ability to understand and validate KPIs and reporting logic.
Excellent communication, collaboration, and problem-solving skills.
Ability to work independently, proactively, and across cross-functional teams including R&D and Data.

Responsibilities

Design and execute comprehensive test plans to validate data pipelines, transformations, and business logic across onshore and offshore environments.
Support R&D teams by investigating and triaging incoming tickets that require deep-diving into sensitive PHI/PII data, ensuring findings are handled with the highest standards of compliance and confidentiality.
Collaborate closely with R&D and Engineering teams to reproduce issues, trace root causes through data, and accelerate resolution cycles.
Perform data validation and reconciliation across multiple systems, ensuring accuracy, consistency, and regulatory alignment.
Execute automated test scripts for web, mobile, API, and data quality testing.
Collaborate with Analytics and Development teams to identify test cases, define test strategies, and ensure accuracy of data used for reporting and KPIs.
Identify, document, and track defects, following through to resolution with both Data and R&D stakeholders.
Maintain comprehensive test documentation including STP, STD, and STR for data validation and automation processes.
Monitor scheduled jobs and alerting systems for pipeline failures.
Leverage AI/ML-based testing techniques, including prompt validation, model behavior testing, and intelligent defect detection, to accelerate quality at scale.
Validate KPIs, metrics, and business rules implemented in dashboards and similar BI tools.
Ensure alignment between data definitions, business expectations, and actual system outputs.
Translate complex technical data issues into clear, business-friendly language for Client Success and Product teams.
Partner with Data Engineering and Analytics teams to ensure data used for reporting is accurate and fit for purpose.
Serve as the QA bridge between globally distributed engineering teams — facilitating communication, test coordination, and knowledge transfer across time zones.
Actively support developers with debugging, log analysis, and root cause identification during data incidents.
Work closely with the Client Success team to translate technical findings into business impact — and business requirements into testable acceptance criteria.