Quality engineering strategy
Practical test strategies that focus effort on the right risks and make quality a shared engineering responsibility.
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Let’s talk ↗QA Automation Lead · Quality Engineering
Building confidence
into complex systems.
I’m Kevin Benoit. I help engineering teams improve release confidence through better automation, data validation, and practical quality strategy.
QUALITY SIGNALACTIVE
11+years building
quality systems
quality systems
UI · API · DATATest architecture
STRATEGY → DELIVERYLeadership scope
Based in Canada · Working across teams & systems01 · QUALITY, BY DESIGN
01 Point of view
Quality isn’t a final checkpoint.
It’s how teams build and release with confidence.
For more than 11 years, I’ve worked in web application testing, automation, and team leadership. My goal has always been to help teams understand risk earlier and make better release decisions.
Today, I focus on the bigger picture around testing: how strategy, architecture, data, tools, and people work together to improve quality at scale.
02 Expertise
Where quality meets
engineering strategy.
I connect hands-on technical work with the strategy and team practices needed to make quality sustainable.
Automation architecture
Maintainable UI, API, and integration automation built around product risk instead of raw test counts.
↗Data & intelligence QA
End-to-end validation for data pipelines, semantic models, Power BI, Microsoft Fabric, and AI-enabled products.
↗Quality leadership
Coaching teams, improving delivery practices, and turning technical quality risks into decisions leaders can act on.
↗TECHNOLOGY IN CONTEXT
Selenium · Testim · API automation · Power BI · Microsoft Fabric · AI validation
03 Selected work
Systems, not
test scripts.
Examples of the quality problems I solve, the choices I make, and the value those decisions create for teams.
01
Quality modernization
From reactive testing to an engineering quality system
THE CHALLENGE
Scattered checks and late feedback made release risk hard to see and expensive to manage.
THE APPROACH
I brought test coverage, ownership, automation, and release signals together in one risk-based strategy.
THE VALUE
Teams got faster feedback, clearer ownership, and a quality practice that could grow with delivery.
02
Automation architecture
Reliable automation across UI and API
THE CHALLENGE
Brittle end-to-end tests created noise, slowed down diagnosis, and demanded too much maintenance.
THE APPROACH
I rebalanced coverage across Selenium, Testim, API, and integration layers, with shared patterns and clear ownership.
THE VALUE
Teams gained a more dependable test signal and an automation foundation that could evolve without constant rewrites.
03
Data platform assurance
Confidence in analytics, Power BI, and Fabric
THE CHALLENGE
A dashboard can be online and still show incomplete, stale, or misleading information.
THE APPROACH
I validate the full path from source data and transformation rules to semantic models, refreshes, and user-facing reports.
THE VALUE
The result is more trustworthy reporting and a clearer view of where data quality risks remain.
04 Leadership approach
Clarity creates
momentum.
Strong quality leadership isn’t about owning every test. It’s about making risk visible, building team capability, and helping people make confident decisions.
01
Make risk clear
Turn technical signals into decisions that teams and leaders can act on.
02
Design for ownership
Build practices that engineering teams understand, trust, and sustain.
03
Strengthen the system
Improve the tools and architecture while helping the people who use them grow.
ALWAYS OPEN TO A GOOD CONVERSATION
Complex systems deserve
thoughtful conversations.
I enjoy connecting with engineering and product leaders who are working through complex quality, automation, and data challenges. If that sounds like you, let’s connect.
Connect on LinkedIn ↗