SQA Manager

Datacolor, a global leader in color management solutions, provides software, instruments and services to improve the precision, performance and efficiency of your color workflow. For over five decades, Datacolor has earned our reputation as a trusted leader by delivering unmatched capabilities that rapidly address the full spectrum of color challenges in textile and apparel, paint and coatings, automotive, plastics, photography and videography, and other industries.

Our global teams provide sales, service and support in over 100 countries throughout Europe, the Americas and Asia.

For more information, visit .

To support our business, we are looking for a looking for a forward-thinking Software Quality Manager to lead our QA Engineering team through a pivotal transformation.

Position Summary:

We manage a complex ecosystem comprising critical legacy applications and cutting-edge new products. We need a leader who can respect the stability of the past while aggressively architecting the future. You are not just a manager; you are a technical architect of quality. Your primary mandate is to minimize manual intervention by designing an intelligent, automated testing ecosystem. You will spearhead the integration of Artificial Intelligence (AI) into our SQA workflows to generate test cases, optimize pipelines, and predict failures before they reach production.

Essential Duties and Responsibilities:

1. Strategic Leadership & Management

• Lead, mentor, and grow a team of QA Engineers (Manual and Automation) working across diverse tech stacks.
• Define the Quality Strategy for both Legacy Systems (maintenance, regression, stability) and Greenfield Applications (speed, agility, scalability).
• Foster a “Quality as Code” culture, bridging the gap between developers and QA.

2. AI-Driven Automation & Architecture

• Architect and implement a robust automation framework that supports web, API, and backend testing.
• AI Integration: Champion the use of Generative AI and Machine Learning tools to create self-healing test scripts, automate test data generation, and perform visual regression testing.
• Build and maintain “Intelligent Pipelines” within our CI/CD environment (GitHub/Azure DevOps) that utilize AI to intelligently select and execute tests based on code changes (Test Impact Analysis).

3. Product Collaboration & Customer Focus

• Partner deeply with Product Owners during the requirements phase. You will help “flesh out” complex use cases and acceptance criteria to ensure testability is baked in from day one.
• Ensure SQA team translates customer feedback and support tickets into actionable test scenarios. Ensure the team understands not just how the software works, but why the customer uses it.
• User Acceptance: Facilitate UAT phases that mimic real-world customer behaviors, ensuring our legacy updates and new features provide a seamless user experience.

4. Release Management & DevOps

• Pipeline Ownership: Manage the release process and ensure smooth CI/CD transitions from development to production.
• Environment Management: Oversee the stability and data integrity of staging, QA, and production environments in Azure.

5. Metrics & Reporting

• Define and track KPIs related to automation coverage, defect leakage, and release velocity.
• Utilize AI-driven analytics to identify patterns in defect data and predict potential hot spots in the codebase.

Experience & Qualifications:

• Experience: 7+ years in Software Quality Assurance with at least 3+ years in a people management or technical lead role.
• Automation Expertise: Deep, hands-on experience building automation frameworks from scratch (using tools like Selenium, or Playwright).
• Coding Skills: Proficiency in at least one scripting language (Python, C#, or TypeScript). You must be able to do code reviews for your team.
• AI/ML in QA: Proven experience or demonstrable knowledge in applying AI to QA (e.g., using LLMs for test case generation, Copilot for code assistance, or commercial AI testing tools).
• CI/CD Integration: expert-level understanding of integrating automated suites into build pipelines (GitHub Actions, Azure DevOps).

Preferred Qualifications:

• Experience managing QA for Monolithic to Microservices migrations.
• Familiarity with Containerization (Docker, Kubernetes) and cloud environments (AWS/Azure).
• Experience implementing Test Impact Analysis (TIA) to reduce regression cycle times.

The ideal candidate profile:

• The Hybrid: You are comfortable reading C++/Legacy code logs in the morning and writing Python scripts for an AI agent in the a