Quality Centre of Excellence Leader

About Us:

insightsoftware is a global provider of reporting, analytics, and performance management solutions that unlock the potential of business data and transform the way finance and data teams operate. We empower leaders from over 32,000 organizations to make timely and intelligent decisions. Our comprehensive solutions span Financial Planning and Analysis (FP&A), Controllership, and Data and Analytics. We deliver finance teams the insights required to navigate any economic climate and drive greater financial intelligence, while increasing productivity, visibility, accuracy, and compliance. Learn more at insightsoftware.com.

Job Description:

We are looking for an accomplished engineering leader and testing expert who will establish and lead a Quality Center of Excellence (QCoE) to transform how ~700 engineers across insightsoftware approach automated testing and quality practices.

This is not a traditional QA management role. You will lead a small team of test automation experts who partner directly with product engineering teams — not to own their testing, but to diagnose quality gaps, teach sustainable testing practice, and build lasting capability. A critical gap we see across the organization is over-reliance on slow, brittle end-to-end tests and under-investment in the acceptance and contract-testing layers that should catch most regressions faster and more reliably. You will help teams build healthy test pyramids, achieve fast feedback loops, and reach high/elite DORA outcomes (elite deployment frequency, low change failure rates, and fast lead times).

You will operate as a program manager and strategic advisor: aggregating quality maturity signals across the portfolio, prioritizing where the QCoE engages based on risk, and reporting portfolio-level insights to engineering leadership so they can drive investment in the teams and practices that matter most. This role requires influence without authority, deep expertise in test automation architecture, and a commitment to building sustainable, healthy testing practices at scale. You will report directly to the VP of Engineering, giving you strategic visibility and the authority to prioritize QCoE engagement across the portfolio.

Your team will help engineering teams leverage AI-powered testing tools — intelligent test generation, test prioritization, self-healing test automation, and predictive quality analytics — as force multipliers. Teaching teams when and how to use these tools effectively, grounded in sound testing architecture, is part of the QCoE mission.

Responsibilities

Portfolio Assessment & Risk Management

• Define and maintain a quality maturity model/scorecard across all engineering teams, measuring test pyramid health (unit vs. acceptance vs. integration vs. E2E ratios), automation coverage, test reliability/flakiness, and alignment with DORA metrics.
• Conduct regular portfolio reviews to identify systemic quality risks, gaps, and anti-patterns — e.g., teams over-indexing on E2E tests, missing acceptance-layer testing, or carrying high technical debt in test infrastructure.
• Aggregate quality signals across the organization and translate technical findings into business risk language for engineering leadership; establish a regular reporting cadence (e.g., quarterly) to communicate quality maturity trends and engagement impact.
• Use maturity data and risk assessment to prioritize where the QCoE engages next — ensuring scarce coaching resources are allocated based on strategic impact and risk, not by whoever escalates loudest.

Test Pyramid & Test Architecture Coaching

• Partner directly with engineering teams to diagnose their current testing approach, identify pyramid imbalances, and co-design a healthier mix of unit, acceptance/contract, integration, and E2E tests.
• Build and teach reusable test automation patterns, frameworks, and 'golden path' templates that engineering teams adopt themselves — focusing on contract/consumer-driven testing (e.g., Pact), API/service-level testing, and right-sized functional test suites.
• Help teams reduce brittle, slow E2E test suites by building out acceptance and contract-testing layers that provide faster, more reliable feedback and reduce the need for end-to-end test coverage.
• Coach teams on test sustainability: identifying and remediating flaky tests, designing for test maintainability, and building test infrastructure that scales with the codebase.

DORA-Driven Engagement & Capability Building

• Work with Engineering Managers to identify gaps in DORA outcomes (deployment frequency, change failure rate, lead time, MTTR) and prescribe automation practice changes to improve them; make the connection explicit between test pyramid health and deployment velocity.
• Run hands-on enablement: bootcamps, office hours, embedded pairing sessions, and internal certification/maturity models for test automation practice that teams can self-assess against.
• Establish a test automation practice maturity model to benchmark teams' progress over time and celebrate wins; create a culture where excellent automation practice is the norm, not the exception.

AI-Enhanced Testing & Tool Evaluation

• Evaluate, pilot, and guide adoption of AI-powered testing tools and agentic solutions — including intelligent test generation, test prioritization, self-healing test automation, and predictive quality analytics.
• Coach teams on when and how to use AI-driven quality tooling effectively; establish guardrails so AI tools amplify good testing practices rather than substitute for sound test architecture.
• Stay current with emerging AI/agentic testing solutions and communicate opportunities and risks to leadership.

Leadership & Stakeholder Alignment

• Hire, manage, and mentor a small team of senior test automation engineers who bring deep expertise to coaching and technical problem-solving.
• Build and maintain a culture of speed, excellence, collaboration, mentorship, and psychological safety within the QCoE; model the coaching and enabling mindset you expect your team to embody.
• Collaborate across product, engineering, and operations; negotiate and align with Engineering Managers/Directors on remediation roadmaps when teams' practices pose delivery or reliability risk.

Qualifications

Competencies

To perform the job successfully, an individual should demonstrate the following competencies:

• Deep Quality & Test Architecture Expertise — Mastery of test pyramid design, contract/consumer-driven testing, API/service-level testing, and test sustainability; proven ability to diagnose and fix test anti-patterns.
• Coaching & Enablement Mindset — Strong desire to teach and build capability in others rather than own execution; experienced at influencing engineering teams without formal authority; comfort with ambiguity and iterative problem-solving.
• Program Management & Portfolio Thinking — Able to aggregate data across many teams, prioritize scarce resources against risk, and drive alignment with senior stakeholders; experienced at turning technical findings into business-relevant language.
• DORA-Fluent — Working knowledge of DORA metrics (deployment frequency, change failure rate, lead time, MTTR) and how test automation practice maturity drives them, especially for multi-tenant SaaS products.
• Leadership & Communication — Excellent written and oral communication; strong presence with senior engineering leadership and product teams; demonstrates psychological safety, openness to feedback, and a learning mindset.
• Technical Fluency with AI/Agentic Solutions — Foundational understanding of AI concepts, prompt engineering, and ability to evaluate AI-powered testing tools; comfort learning and experimenting with emerging technologies.
• Discipline & Perseverance — Focus and commitment to solving complex problems through to completion; relentless pursuit of sustainable, healthy testing practices.
• Results Orientation — Strong bias toward action; able to set priorities, deliver measurable outcomes, and demonstrate impact through metrics and stakeholder feedback.

Qualifications & Experience

• Bachelor's degree in Computer Science, Computer Engineering, or related technical discipline, or equivalent professional experience.
• Hands-on testing and software quality assurance experience in fast-paced, iterative environments, including multi-tenant SaaS products.
• Experience testing SaaS/multi-tenant products deployed on-demand with continuous deployment cadence, including familiarity with: progressive deployment patterns (canaries, feature flags, staged rollouts), testing strategies that account for multiple versions running simultaneously, and how continuous deployment shapes the balance of test types (fast feedback loops vs. comprehensive coverage).
• Deep expertise in test pyramid strategy and how to rebalance testing toward fast, reliable feedback — with hands-on experience across unit, acceptance/contract, and integration testing layers, and demonstrated track record of helping teams reduce over-reliance on E2E suites.
• Proven experience coaching or consulting with engineering teams on testing best practices — influence-without-authority is the primary skill, not direct execution or ownership of testing.
• Expert background in test automation with a demonstrated record of tactical execution and strategic leadership in test automation and quality engineering programs.
• Coding proficiency in at least one modern language (e.g., C#, Java, TypeScript, Python).
• Experience with CI/CD principles, tools, and infrastructure; solid understanding of version control and source control management tools (e.g., GitHub, Azure DevOps).
• Hands-on experience with cloud computing platforms (AWS, Azure, GitHub), containers (Docker, Kubernetes), and multi-tiered infrastructure.
• Experience working in Agile/Scrum development environments and with Agile metrics (or willingness to learn DORA metrics deeply).
• Experience evaluating, piloting, or implementing AI-powered testing tools or agentic solutions for test automation, test data generation, or quality intelligence.
• Experience building or presenting quality maturity scorecards/dashboards and communicating technical risk to VP+ or leadership audiences.
• Desirable: Experience with REST APIs, databases, and SQL; experience building or mentoring test automation frameworks; experience in financial software, SaaS, or similar complex product domains.

 

 

 

The salary range in United Kingdom for this position is 97,000.00 to 122,000.00 GBP Annual.

For sales roles, this range includes the commission target. For non-sales roles, this is a base salary only range; additional bonus eligibility may apply.

Your specific offer within this range will be determined by your skills, experience, and qualifications.

We are committed to pay transparency and fair compensation practices. If you have questions about our compensation approach, please don't hesitate to ask during the interview process.

Additional Information

All your information will be kept confidential according to EEO guidelines.

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