QA Engineer

Quality Assurance Engineer

Siftwell is seeking a Quality Assurance Engineer to help ensure the accuracy and reliability of our healthcare data and software products. Reporting to the VP of Engineering, you will build automated approaches to data validation that identify incomplete, inaccurate, inconsistent, or unexpected customer data.

You will also support Siftwell's customer-facing analytics application by triaging and reproducing bugs, documenting findings, and equipping engineers to resolve issues efficiently. As our customer base grows, you will help establish scalable testing, validation, and issue-management practices.

This is a hands-on role for someone who brings curiosity, healthy skepticism, and high ownership to quality. You will look beyond whether the code ran successfully to determine whether the data inputs, outputs and customer experience make sense. Over time, you may also contribute to small engineering tickets, product enhancements, and other technical initiatives as needed.

This position is remote within the United States and operates primarily during U.S. Eastern Time business hours. Occasional travel may be required for company meetings and team events. Employment is contingent upon successful completion of a pre-employment background check.

• Build and maintain automated validation processes for customer data inputs, transformations, and outputs.
• Replace manual checks and one-off scripts with repeatable, scalable, automated, and well-documented quality-assurance methods.
• Identify data that is incomplete, inconsistent, inaccurate, or outside expected parameters and clearly communicate potential issues to the appropriate stakeholders.
• Investigate discrepancies across source data, processing logic, and delivered outputs to determine where issues originate.
• Develop and maintain test plans, test cases, regression tests, validation rules, and supporting documentation.
• Perform functional, integration, and regression testing for Siftwell software products and data pipelines.
• Triage, reproduce, document, and track software bugs reported by customers and internal stakeholders.
• Translate loosely defined issue reports into clear, actionable tickets that enable engineers to diagnose and resolve problems efficiently.
• Partner with Engineering, Data Science, Product, and Customer Success to assess issue severity, clarify expected behavior, and support timely resolution.
• Help establish and continuously improve Siftwell's QA processes, tools, standards, and operating practices as the company and customer base grow.
• Monitor recurring defects and data-quality patterns, identify root causes, and recommend opportunities for greater automation or prevention.
• Contribute to smaller engineering tickets, product enhancements, or technical projects based on team needs and individual interest.
• Handle protected health information and other sensitive data in accordance with Siftwell's security, privacy, and compliance requirements.

Required:

• Bachelor's degree required plus a minimum of 5 years of relevant work experience;
  Master's degree or relevant professional certification preferred.
• Minimum of 5 years of experience in software quality assurance, data quality, test engineering, or a closely related technical role, including testing data pipelines, analytics platforms, machine-learning products, or other data-intensive applications.
• Experience designing and implementing automated API, backend, and end-to-end application tests, data-validation frameworks, and repeatable QA processes.
• Proficiency in Python or another scripting language used for testing, automation, and data validation, with working knowledge of SQL and relational databases.
• Proficiency in automated unit and integration testing frameworks and tools, like Playwright, Selenium, Vitest, and pytest.
• Experience performing functional, integration, and regression testing, including reproducing, isolating, documenting, and communicating software defects.
• Strong analytical and problem-solving skills, with the judgment to look beyond whether code executed successfully and assess whether the underlying data and results make sense.
• High ownership, attention to detail, and strong communication skills, with the ability to work independently and collaborate effectively across technical, product, and customer-facing teams.

Preferred:

• Familiarity with software development practices, version control, and continuous integration and deployment workflows.
• Experience establishing or improving QA processes within a startup or growth-stage company.
• Experience working with healthcare data, protected health information, and HIPAA requirements, or within another regulated-data environment.
• Interest in expanding into broader software engineering responsibilities over time.