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# Senior Software Development Engineer in Test

AI Summary Varicent is hiring a Senior Software Development Engineer in Test to lead quality engineering for its AI-powered ELT platform. The role owns test strategy across unit, integration, API, UI, and data-validation layers while building scalable automation frameworks and CI/CD quality gates. The successful candidate will partner closely with engineering, product, and QA stakeholders, mentor peers, and improve reliability, coverage, and delivery speed through measurable quality practices. The position also requires implementing AI-enabled or agentic workflows for testing, failure analysis, reporting, and engineering operations. Strong programming, SQL, distributed-systems testing, and test-architecture experience are central to success.[Apply for this job](#job-application)[View company](https://jobicy.com/company/varicent.md)ShareRemote from[Canada](https://jobicy.com/job-region/canada.md)SalaryCAD 101k–132,500 / yrDepartment[QA & Testing](https://jobicy.com/categories/qa-testing.md)EmploymentFull TimeExperienceSeniorPublished13 Nov 2026Apply before13 Dec 2026Listing views28Application actions3Application toolkit

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Opportunity details

## About this role.

At [Varicent](https://jobicy.com/company/varicent.md), we’re not just transforming the Sales Performance Management (SPM) market—we’re redefining how organizations achieve revenue success. Our cutting-edge SaaS solutions empower revenue leaders globally to design smarter go-to-market strategies, maximize seller performance, and unlock untapped potential. Varicent stands at the forefront of innovation, celebrated as a market leader in the 2025 Forrester Wave Report for SPM, 2023 Ventana Research Revenue Performance Management (RPM) Value Index, Gartner Peer Insights, 2024 Gartner SPM Market Guide, and G2. Our solutions are trusted by a diverse range of global industry leaders like T-Mobile, ServiceNow, Wawanesa Bank, Shaw Industries, Moody’s, Stryker and hundreds more. Here’s why you’ll thrive at Varicent:

* Innovate with Purpose: Build impactful solutions for customers worldwide.
* Join Excellence: Work in a diverse, collaborative, and innovative team.
* Shape the Future: Lead in redefining revenue optimization.
* Grow Together: Unlock your potential in a supportive environment.

Join us at Varicent—where your talent and ambition meet limitless opportunities for success!

Summary of the Role and Team

As a Senior Software Developer in Test (Senior SDET), you will play a critical role in ensuring the quality, reliability, scalability, and performance of Varicent’s AI-powered ELT (Extract, Load, Transform) platform.

Working within a cross-functional team of Software Engineers, QA professionals, and Product Managers, you will lead the evolution of test automation practices, establish quality engineering standards, and design scalable testing solutions that support rapid and reliable software delivery.

This role combines software development, test architecture, automation engineering, technical leadership, and AI-driven innovation. You will help shape how quality is built into the product while advancing the use of agentic AI workflows to improve testing efficiency and engineering productivity.

What You Will Be Doing

* Define and lead the test strategy across unit, integration, API, UI, and data-validation testing layers

* Design, build, and maintain scalable automated test frameworks for web applications, APIs, backend services, and data pipelines

* Integrate automated testing into CI/CD workflows to provide fast feedback, reliable quality gates, and consistent release confidence

* Partner with Software Engineers, Product Managers, and QA team members to build quality into features from design through delivery

* Mentor engineers and contribute to the development of testing standards, automation practices, and code quality expectations across the team

* Design and implement AI-enabled and agentic workflows that automate testing, failure analysis, reporting, and engineering operations

* Analyze quality metrics to identify risks, improve test coverage, reduce flakiness, and increase automation effectiveness

* Evaluate and introduce tools, frameworks, and engineering practices that improve software quality, reliability, and delivery speed

What You Bring

* 5+ years of experience in Software Development, Test Automation, Software Quality Engineering, or a related technical discipline

* Strong programming experience in languages such as Python, JavaScript, or TypeScript, with a focus on maintainable and reusable code

* Experience designing and implementing automated testing frameworks for web, API, backend, or data-intensive applications

* Experience building, maintaining, and optimizing CI/CD pipelines using tools such as Jenkins, GitHub Actions, GitLab CI, or similar platforms

* Strong knowledge of API testing, distributed systems, and data validation methodologies

* Advanced SQL skills with experience validating databases, data pipelines, ETL, or ELT processes

* Experience using or implementing AI-enabled tools, automation workflows, agentic systems, or LLM-powered engineering solutions

* Strong communication, mentorship, collaboration, and technical leadership skills, with English proficiency at a B2 level or above

Success Outcomes

First 30 Days

* Develop a strong understanding of the platform architecture, product workflows, testing practices, and development processes

* Set up development, testing, and automation environments

* Assess the current testing strategy, automation coverage, CI/CD pipelines, and quality risks

* Build working relationships with Software Engineering, Product, and QA stakeholders

Within 60 Days

* Take ownership of test automation for a key product area or service

* Deliver initial improvements to automation coverage, testing efficiency, or pipeline reliability

* Recommend a roadmap for improving testing frameworks, coverage, and quality processes

* Begin contributing to technical mentorship, knowledge sharing, and testing best practices within the team

Within 90 Days

* Lead testing strategy and automation initiatives for a defined product area

* Implement measurable improvements in test reliability, execution speed, and automation effectiveness

* Establish quality metrics and testing standards used across the team

* Drive technical discussions around architecture, testing approaches, and quality engineering practices

* Deliver an AI-enabled or agentic automation workflow that reduces manual testing effort, improves triage efficiency, or accelerates delivery processes

For this role, the estimated annual base salary range is between 101,000.00 – 132,500.00 CAD. In addition to base salary, our compensation package may include bonuses, commissions for eligible sales roles, and a comprehensive benefits package. The actual base salary will vary based on factors including individual qualifications and market data, as objectively assessed during the interview process.

 

This posting is for a new vacancy.

 

This hiring process utilizes artificial intelligence tools to assist in candidate screening and assessment. Our AI tools are designed to complement — not replace — human decision-making.

 

Overview of Benefits:

 

*  Health & Wellness — Comprehensive medical, dental, and vision coverage tailored to your local needs
* Time Off — PTO and public holidays to rest, recharge, and do what matters most
* Volunteer Days — Dedicated time to give back and support the communities that matter to you
* Ignite Days — Dedicated learning days to support continuous growth, skill development, and professional learning
* Financial — Compensation that reflects your market and your value
* Retirement — Retirement plans designed to help you build long-term financial security
* Tuition Assistance — Invest in your growth with support for continuing education and professional development
* Flexibility — Work where you thrive, with remote and hybrid options available across most regions

Varicent is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. If you require accommodation at any time during the recruitment process please email accomodations@varicent.com

Varicent is also committed to compliance with all fair employment practices regarding citizenship and immigration status. By applying for a position at Varicent and/or by using this portal, you declare and confirm that you have read and agree to our[Job Applicant Privacy Notice](https://www.varicent.com/recruitment-portal-privacy-notice) and that the information provided by you as part of your application is true and complete and includes no misrepresentation or material omission of fact

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[Apply now >](https://jobicy.com/jobs/162052-senior-software-development-engineer-in-test.md)

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![Upload CV](data:image/svg+xml;base64,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)

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## Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

### Job Complexity

5/5EasyHard

### Pace & Pressure

4/5RelaxedFast-paced

### Autonomy Level

5/5GuidedFull ownership

### Communication Load

4/5IndependentCollaborative

AI insightThis is a senior technical leadership role spanning test architecture, automation, CI/CD, data validation, and AI-enabled engineering workflows. Success requires independent ownership of quality strategy and the ability to influence cross-functional engineering practices.

## Salary analysis

Estimated compensation compared with the broader CA market for similar roles.

Estimated job median (per year)Market rateC$116,750CA market range (per year)C$105k–C$145k0C$159.50k

AI insightThe employer explicitly states an annual base salary range of CAD 101,000 to CAD 132,500, with a midpoint of CAD 116,750. A reasonable estimated annual market range for a senior SDET in the Toronto/Canada market is CAD 105,000 to CAD 145,000; these are AI estimates rather than verified salary research.

## Core skills

Skills and capabilities most closely associated with this opportunity.

[Test Automation](https://jobicy.com/jobs?search_keywords=Test%20Automation.md)[Quality Engineering](https://jobicy.com/jobs?search_keywords=Quality%20Engineering.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md)[JavaScript](https://jobicy.com/jobs?search_keywords=JavaScript.md)[TypeScript](https://jobicy.com/jobs?search_keywords=TypeScript.md)[API Testing](https://jobicy.com/jobs?search_keywords=API%20Testing.md)[CI/CD](https://jobicy.com/jobs?search_keywords=CICD.md)[Jenkins](https://jobicy.com/jobs?search_keywords=Jenkins.md)[GitHub Actions](https://jobicy.com/jobs?search_keywords=GitHub%20Actions.md)[SQL](https://jobicy.com/jobs?search_keywords=SQL.md)[Data Validation](https://jobicy.com/jobs?search_keywords=Data%20Validation.md)[ELT Testing](https://jobicy.com/jobs?search_keywords=ELT%20Testing.md)[Distributed Systems](https://jobicy.com/jobs?search_keywords=Distributed%20Systems.md)[AI Automation](https://jobicy.com/jobs?search_keywords=AI%20Automation.md)[Test Strategy](https://jobicy.com/jobs?search_keywords=Test%20Strategy.md)

Sample interview questionsHow would you define a test strategy for an AI-powered ELT platform?I would map critical business and data flows across unit, integration, API, UI, and pipeline layers, then apply risk-based coverage to the highest-impact transformations and failure modes. The strategy would include data-quality assertions, contract tests, end-to-end smoke coverage, observability, and clear release-quality gates.

What techniques do you use to reduce flaky automated tests?

I first classify failures using test telemetry, logs, retries, and environment signals to separate product defects from test or infrastructure instability. I then remove timing assumptions, use deterministic test data, isolate dependencies where appropriate, improve synchronization, and track flakiness as a visible quality metric.

Describe how you would integrate automated testing into a CI/CD pipeline.

I would create fast, reliable feedback stages beginning with linting and unit tests, followed by API and integration suites, security or quality checks, and targeted end-to-end tests. Tests should produce actionable reports, enforce agreed quality thresholds, and use parallelization and test selection to keep pipeline duration practical.

How do you validate the correctness of data pipelines and ELT transformations?

I validate schemas, completeness, uniqueness, referential integrity, transformation rules, and reconciliation between source and target datasets. I use SQL-based assertions, controlled fixtures, boundary cases, historical comparisons, and monitoring for data drift or unexpected volume changes.

How would you apply AI or agentic workflows to improve quality engineering?

I would start with bounded, measurable use cases such as failure-log classification, test-case generation assistance, defect-triage summaries, and intelligent test selection. Each workflow should retain human review for high-impact decisions, be evaluated against accuracy and time-saved metrics, and integrate securely with engineering tools.

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