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Data Qa Jobs in Quebec (NOW HIRING)

Confidential

General Reporting to the Vice President, Quality Assurance, the incumbent is responsible for the ... Strong skills in management, data analysis, and IT tools * Excellent command of French (spoken and ...

Targeted Talent

Senior QA Engineer

Quebec, QC · Remote

We are looking for an experienced Senior QA Engineer for our client. This is a permanent position ... You'll have the opportunity to work on an amazing platform that combines Data Analytics, and ...

Targeted Talent

Senior QA Engineer

Montreal, QC · Remote

We are looking for an experienced Senior QA Engineer for our client. This is a permanent position ... You'll have the opportunity to work on an amazing platform that combines Data Analytics, and ...

Targeted Talent

Senior QA Engineer

Quebec, QC · Remote

We are looking for an experienced Senior QA Engineer for our client. This is a permanent position ... You'll have the opportunity to work on an amazing platform that combines Data Analytics, and ...

Targeted Talent

Senior QA Engineer

Montreal, QC · Remote

We are looking for an experienced Senior QA Engineer for our client. This is a permanent position ... You'll have the opportunity to work on an amazing platform that combines Data Analytics, and ...

Mako Fintech

Junior QA Specialist

Montreal, QC · Remote

... understand business, functional and data modifications in scope for each sprint/release ... Recommend and institutionalize QA best practices, methodology and tool * Work closely with the ...

Royal Bank of Canada

Senior QA Analyst

Montreal, QC · On-site

Analyze and troubleshoot issues related to data flows, test execution, system behavior, and ... and QA experience with strong Java knowledge * Strong SQL and relational database knowledge ...

SYSTRA

The role is primarily based in ArcGIS Pro, with data accessed and shared through ArcGIS Enterprise ... Lead the quality assurance and quality control review of cartographic outputs by verifying map ...

Jestais

Maintain test data, environments, and automation frameworks aligned with production configurations ... Mentor junior QA team members on automation best practices and tools when needed. Qualifications ...

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All JobsData Qa JobsData Qa Jobs in Quebec

Data Qa information

What is the data QA role?

A Data QA (Quality Assurance) role involves reviewing and testing data to ensure accuracy, completeness, and consistency. Data QA professionals often use tools like SQL and data validation software to identify errors and verify data integrity within datasets or databases, supporting reliable data analysis and decision-making.

Will AI replace a data analyst?

AI can automate certain data analysis tasks, such as data cleaning and basic reporting, but it is unlikely to fully replace data analysts. Data analysts bring critical thinking, domain knowledge, and interpretative skills that complement AI tools, making their role essential for complex insights and decision-making. Proficiency in tools like SQL, Excel, and data visualization software remains important for the job.

What are top 3 skills for a QA analyst?

A QA analyst should have strong attention to detail, proficiency in testing tools and scripting languages, and good communication skills to document and report issues effectively. Knowledge of software development life cycle (SDLC) and familiarity with automation frameworks are also valuable. These skills help ensure software quality and efficient testing processes.

What is the difference between Data Qa vs Data Analyst?

AspectData QaData Analyst
Required CredentialsBasic understanding of testing tools, some certificationsDegree in data-related fields, certifications like Microsoft or SAS
Work EnvironmentQuality assurance teams, software testing environmentsData analysis teams, business intelligence settings
Employer & Industry UsageTech companies, software development firmsFinance, marketing, healthcare, and other industries
Common Search & ComparisonOften compared for data quality rolesMore focused on data insights and reporting

Data Qa professionals primarily focus on testing and ensuring data quality, often working within QA teams to validate data accuracy and integrity. Data Analysts, on the other hand, analyze data to generate insights, create reports, and support decision-making. While both roles work with data, Data Qa emphasizes quality assurance processes, whereas Data Analysts focus on data interpretation and analysis.

Is QA still in demand?

Quality Assurance (QA) roles, including Data QA, remain in demand as companies prioritize data accuracy and software quality. Skills in testing tools, scripting, and understanding data workflows are valuable, and demand is expected to grow with increasing reliance on data-driven decision-making.
What job categories do people searching Data Qa jobs in Quebec look for? The top searched job categories for Data Qa jobs in Quebec are:
Data Qa jobs near you
Infographic showing various Data Qa job openings in Quebec as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, 1% Temporary, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

QA Lead AI Systems & Models Testing

Jay Analytix

Montreal, QC • On-site

Contractor

Re-posted 18 days ago

Job description

QA Lead AI Systems & Models Testing

Quality Assurance Artificial Intelligence Contract Position

Contract

Montreal, QC

AI / ML Testing

LLM / RAG / LangChain

ABOUT THE ROLE

We are seeking an experienced QA Lead with deep expertise in AI systems testing to join our team on a contract basis in Montreal, Qubec. This role sits at the intersection of quality engineering and artificial intelligence, requiring hands-on proficiency in LLM behavior analysis, RAG pipeline validation, and modern AI orchestration frameworks. You will own the end-to-end test strategy for complex AI products and help define quality standards in a rapidly evolving space.

MUST-HAVE SKILLS

  • Proven QA leadership experience designing and executing test strategies for AI/ML systems or LLM-powered applications.
  • Strong understanding of LLM internals: tokenization, embeddings, attention mechanisms, and inference behavior to anticipate and diagnose failure modes.
  • Hands-on experience with prompt engineering constructing effective prompts, detecting hallucinations, and evaluating outputs across accuracy, tone, coherence, and bias dimensions.
  • Experience testing RAG pipelines and knowledge base integrations, including validation of data quality and retrieval accuracy as they impact model outputs.
  • Familiarity with vector database mechanics: similarity search thresholds, embedding drift, near-duplicate documents, and sparse vs. dense embeddings.
  • Practical experience with LangChain and/or LangGraph able to read chain/graph construction code, identify failure points, and write test harnesses.
  • Ability to validate MCP (Model Context Protocol) integration points, including tool availability and error-handling scenarios.
  • Proficiency applying generative AI evaluation metrics and establishing quality thresholds appropriate for production AI systems.
  • Excellent written and verbal communication in English; bilingualism (English/French) is a plus for the Montreal market.

NICE-TO-HAVE SKILLS

  • Experience with bias detection and safety testing frameworks for AI systems.
  • Exposure to performance and scalability testing of vector databases under high load.
  • Familiarity with CI/CD pipelines for ML model deployment and automated regression testing.
  • Knowledge of responsible AI principles and AI governance frameworks.
  • Contributions to or experience with open-source AI testing or evaluation tooling (e.g., DeepEval, Ragas, PromptFlow).
  • Background in data engineering or data quality practices relevant to AI pipeline inputs.
  • Cloud platform experience (AWS, Azure, or GCP) in the context of deploying or testing AI workloads.

KEY RESPONSIBILITIES

  • Lead design and execution of comprehensive test strategies across AI systems, including prompt evaluation, output quality assessment, and bias/safety analysis.
  • Develop and maintain test harnesses for LangChain and LangGraph-based applications; review chain and graph construction code to proactively surface integration risks.
  • Validate RAG pipeline integrity data ingestion, chunking, retrieval accuracy, and embedding consistency and define edge-case coverage for vector database interactions.
  • Establish and track generative AI quality metrics and thresholds; report on model output quality across multiple evaluation dimensions.
  • Collaborate with ML engineers, data scientists, and product teams to embed quality practices throughout the AI development lifecycle.
  • Document test findings clearly for both technical and non-technical stakeholders.

Contract position based in Montreal, Qubec, Canada On-site / Hybrid