Data QA Engineer
Role summary
Dario is seeking a Data QA Engineer to ensure the quality and accuracy of their data pipelines, transformations, and business logic. This role involves designing and executing test plans, performing data validation, and executing automated tests across various platforms. A key aspect is working with sensitive PHI/PII data, requiring a strong understanding of compliance. The engineer will also leverage AI/ML-based testing techniques, collaborate with R&D, Engineering, Analytics, and Client Success teams, and translate technical findings into business impact. The position requires a Bachelor's degree and 6+ years of experience in QA, test automation, or data quality, with proficiency in programming, query languages, and QA methodologies.
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:
- 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.
Business Logic & Dashboard Validation
- 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.
Cross-Functional Collaboration
- 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.
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.
\*\*\*DarioHealth promotes diversity of thought, culture and background, which connects the entire Dario team. We believe that every member on our team enriches our diversity by exposing us to a broad range of ways to understand and engage with the world, identify challenges, and to discover, design and deliver solutions. We are passionate about building and sustaining an inclusive and equitable working and learning environments for all people, and do not discriminate against any employee or job candidate. \*\*\*
