Director, Quality Engineering

Role Summary

As a Director, Quality Engineering, you will provide strategic, delivery, and people leadership for the Analysis pillar within Ratings Technology. You will be accountable for leading a large, high performing QE organization while delivering complex, business critical Capital Markets platforms in a regulated environment. You will bring deep Capital Markets domain expertise, modern engineering practices, and forward-looking AI capabilities to build and scale intelligent quality systems that go beyond defect detection to defect prevention, continuous feedback, and product excellenceThis role requires a handson leader who balances enterprise level QE strategy with day-to-day delivery execution, stakeholder management, and direct people leadership. You will lead senior engineering and QE leaders, drive a data driven quality culture, and ensure predictable, highquality outcomes across a complex delivery portfolio.

Key Responsibilities

People Leadership & Culture

• Lead, mentor, and develop a distributed organization of senior QE and engineers (50-75+), fostering engagement, accountability, and continuous improvement.
• Build a strong, inclusive culture focused on engineering excellence, operational efficiency, and quality ownership.
• Own talent strategy including hiring, onboarding, performance management, succession planning, and leadership development.
• Navigate and resolve complex interpersonal and organizational challenges with empathy, professionalism, and clarity.
• Lead teams through change, ambiguity, and transformation while maintaining morale and delivery confidence.
• Leverage people, delivery, and engagement metrics to guide coaching, development plans, capacity planning, and conflict resolution.

• Own end to end delivery for a complex, multi??program portfolio supporting Capital Markets and Analytical platforms.
• Ensure consistent, predictable delivery across global, cross??functional teams in regulated financial services environments.
• Apply deep Capital Markets knowledge to drive risk??based quality strategies for data??intensive, market critical systems.
• Balance speed, quality, regulatory compliance, and operational risk in day??to??day delivery decisions.

• Act as a trusted partner to Product, Engineering, Data, Risk, and Compliance leadership.
• Translate quality, delivery, and operational risks into clear business impact for senior and executive stakeholders.
• Represent Quality Engineering in governance forums, audits, and regulatory interactions.

• Lead the evolution from QA to engineering led QE, embedding shift??left, automation first, and continuous testing practices.
• Establish enterprise QE standards, operating models, and tooling strategies.
• Champion TDD, BDD, DevSecOps, and CI/CD??integrated quality practices across teams.

• Drive adoption of AI powered quality engineering, including agentic test generation, defect triage, and predictive quality analytics.
• Define responsible AI usage standards aligned with security, compliance, and auditability.
• Lead test data and data quality strategies, including synthetic data, masking, lineage, migration validation, and cataloging.
• Use quality and delivery data to continuously improve outcomes and organizational effectiveness.

• Own QE budget planning, vendor management, and investment prioritization.
• Measure and improve cost of quality, automation ROI, and delivery efficiency using objective metrics.

• 15+ years in Quality Engineering or Engineering leadership within Financial Services / Capital Markets.
• Proven experience leading leaders and scaling large, complex delivery organizations.
• Demonstrated ability to manage challenging people situations, organizational change, and high??stakes delivery.
• Strong track record of data??driven decision??making across delivery, people management, and operations.
• Deep expertise in automation frameworks, CI/CD, test data management, and AI??enabled testing.
• Excellent executive communication and stakeholder management skills.

• Lead a high impact organization at the intersection of Capital Markets, Analytics, Engineering, Data, and AI.
• Shape both people outcomes and platform quality at enterprise scale.
• Define how modern Quality Engineering operates in a regulated, data??driven financial environment.