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Data Engineer Jobs in Quebec (NOW HIRING)

AppDirect

Senior Data Engineer

Montreal, QC · On-site

About You We're hiring a Senior Data Engineer for Data Insights in Montreal-someone with a Data as a Product mindset who builds production pipelines and models others can trust and reuse. You'll ...

Tecsys Inc.

Data Engineer (DevOps)

Montreal, QC · On-site +1

If you thrive on tackling interesting challenges with continuous learning opportunities, then Tescys could be a good fit for you! We're looking for a Data Platform Engineer (DevOps) to join our ...

Wepoint

Data Architect (Big Data & Azure)

Montreal, QC · On-site

Oversee technological choices and implementation patterns for data engineering teams (partitioning, optimization, governance, performance); * Contribute to the definition of data quality, security ...

Pomerleau

Sr. Data Engineer

Montreal, QC · Hybrid

General Information Press space or enter keys to toggle section visibility Job Location * Montreal, QC Date Published 02-Sep-2026 Department Innovation & Systems Employment Type Permanent Working ...

Caeus

Data Engineering Specialist

Montreal, QC · On-site

We are looking for a Senior Data Platform Engineer with strong hands-on coding skills and solid experience in modern data engineering. The ideal candidate has experience with Python, Spark, Git ...

Archera

Software Engineer, Data Quality

Quebec, QC · Remote

Software Engineer, Data QualityCompany Overview Archera empowers organizations of all sizes to optimize their cloud costs through unique, short-term, insured commitments. Thousands of customers rely ...

AlayaCare

Staff Data Developer

Montreal, QC

Reporting to the Director of Data Engineering, you will design and implement scalable, complex data pipelines and infrastructure to power our data products. As a senior member of the team, you'll ...

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Showing results 21-40

All JobsData Engineer JobsData Engineer Jobs in Quebec

Data Engineer information

See Quebec salary details

$60K

$122.6K

$181K

How much do data engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for data engineer in Quebec is $122,622.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,000.00 and $142,500.00 per year, depending on experience, location, and employer.

What is a data engineer?

Data Engineers are IT professionals who design, construct, install, and maintain large-scale processing systems and other infrastructure for collecting, storing, and analyzing data. They build and optimize data pipelines and architectures that allow organizations to efficiently access and use data for business insights. Data Engineers work closely with data scientists, analysts, and other stakeholders to ensure that data is reliable, accessible, and secure. Their responsibilities often include working with databases, cloud platforms, and big data tools.

What are the key skills and qualifications needed to thrive as a data engineer, and why are they important?

To thrive as a Data Engineer, you need a strong background in computer science, data modeling, and programming languages such as Python or Java, often coupled with a relevant degree. Familiarity with ETL tools, big data frameworks (like Hadoop or Spark), and cloud platforms (such as AWS or Azure) is typically required, along with certifications like AWS Certified Data Analytics. Strong problem-solving skills, attention to detail, and effective communication set exceptional data engineers apart. These skills and qualities are essential for building robust data pipelines, ensuring data quality, and supporting data-driven decision-making across organizations.

What does a data engineer do?

The job duties of a data engineer involve helping with the development of systems, software, and infrastructure used to process, store and analyze data. Your responsibilities in this career include working to install data management software. Your employer may expect you to perform maintenance and install updates to all software and systems that they use for data acquisition, management, and analysis. Data engineers also analyze existing data systems to find ways to improve efficiency and accessibility. You then suggest upgrades or changes based on your assessment.

How do data engineers typically collaborate with data scientists and analysts within an organization?

Data Engineers play a crucial role in ensuring that Data Scientists and Analysts have reliable, well-structured data for their projects. This collaboration often involves building and maintaining data pipelines, optimizing data storage solutions, and troubleshooting data quality issues. Regular communication and agile teamwork are common, with Data Engineers frequently participating in meetings to understand analytical requirements and adjust data processes accordingly. By working closely together, these teams can quickly iterate on data models and deliver actionable insights to drive business decisions.

What is the difference between Data Engineer vs Data Scientist?

AspectData EngineerData Scientist
Primary FocusBuilding and maintaining data pipelines and infrastructureAnalyzing data to extract insights and create models
SkillsSQL, ETL, programming (Python, Java), database managementStatistics, machine learning, data analysis, programming (Python, R)
Work EnvironmentData warehouses, cloud platforms, backend systemsData analysis environments, research labs, visualization tools
Common ToolsApache Spark, Hadoop, Airflow, SQLJupyter, RStudio, Tableau, scikit-learn

Data Engineers focus on creating and maintaining the infrastructure that allows data to be collected, stored, and processed efficiently. Data Scientists analyze this data to generate insights, build predictive models, and support decision-making. While their skills overlap, Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior-level role that requires experience with programming, databases, and data pipeline tools. Entry-level positions may be available for those with relevant internships or strong foundational skills, but most data engineering roles demand several years of experience or advanced knowledge of tools like SQL, Python, and cloud platforms.

What is the role of a data engineer?

A data engineer designs, builds, and maintains data pipelines and infrastructure to collect, process, and store large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible and reliable for analysis and decision-making.
More about Data Engineer jobs

What are the most commonly searched types of Data Engineer jobs in Quebec?

The most popular types of Data Engineer jobs in Quebec are:

What are popular job titles related to Data Engineer jobs in Quebec?

For Data Engineer jobs in Quebec, the most frequently searched job titles are:

What job categories do people searching Data Engineer jobs in Quebec look for?

The top searched job categories for Data Engineer jobs in Quebec are:

What cities in Quebec are hiring for Data Engineer jobs?

Cities in Quebec with the most Data Engineer job openings:

What are popular job titles related to Data Engineer jobs in QC?

For Data Engineer jobs in QC, the most frequently searched job titles are:

Data Engineer jobs near you
Infographic showing various Data Engineer job openings in Quebec as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 82% Full Time, 13% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $122,622 per year, or $59 per hour.

Senior Data Engineer

Montreal, QC • On-site

AppDirect
IT Services • 501 - 1,000 employees
Learn more about AppDirectexternal

Full-time

Re-posted 12 days ago

Key responsibilities

  • Design, build, and evolve the lakehouse data platform, including models and pipelines on Snowflake, dbt, and Databricks, to provide reliable and governed data products.

  • Translate product and business requirements into data models and pipelines, working with stakeholders to ensure correct implementation of domain logic in production.

  • Migrate legacy ETL processes to modern streaming and incremental pipelines, and operate and tune Snowflake for reliability, efficiency, and cost management.

Job description

Pour la version francaise de cette description de poste, veuillez consulter le lien suivant / For the French version of this job description, please refer to the following link:

  • Ingenieur(e) de donnees senior

About AppDirect

Become a digital, global citizen and enable the new generation of digital entrepreneurs around the world.  AppDirect offers a subscription commerce platform to sell any product, through any channel, on any device - as a service.  We power millions of subscriptions worldwide for organizations.  We do this by our values-driven culture-one that enables you to Be Seen, Be Yourself, and Do Your Best Work.

About the Data Insights Team

Our mission is to unify data from every business unit into a governed lakehouse and semantic layer, powering analytics, AI, reports, data sharing, and both internal and customer-facing dashboards.

About You

We're hiring a Senior Data Engineer for Data Insights in Montreal-someone with a Data as a Product mindset who builds production pipelines and models others can trust and reuse.

You'll build production data products and lakehouse pipelines that power analytics and both internal and customer-facing dashboards-partnering across engineering and product, establishing clear data contracts, and leaving patterns others can reuse.

What You'll Do and How You'll Make an Impact

  • Platform Architecture & Modeling: Design, build, and evolve the lakehouse data platform-reusable models and pipelines on Snowflake + dbt, with Databricks workloads where they fit-so analytics and product teams get reliable, governed data products.
  • Requirements & Stakeholder Partnership: Translate product and business requirements into data models and pipelines-working with PMs, BUs, and engineers so domain logic lands correctly in production.
  • Pipeline Modernization: Migrate legacy ETL processes to modern, efficient streaming and incremental pipelines, choosing Snowflake or Databricks based on fit.
  • Snowflake Performance & Cost: Operate and tune Snowflake for reliability and efficiency-warehouse sizing and utilization, clustering/partitioning where it pays off, and visibility into credit spend so scale doesn't mean runaway cost.
  • AI-Assisted Operations: Apply AI-assisted development tools and spec-driven workflows to design, automate, and ship data pipelines and platform.
  • Self-Service Enablement: Facilitate scoped data onboarding and empower business unit engineers to build their own data products on top of our platform.
  • Customer-Facing Data Products: Build and evolve data behind customer-facing products-including the reporting service and App Insights-so pipelines and models deliver trustworthy product experiences.
  • Data Quality & Trust: Ensure data quality by driving and implementing robust data governance, automated testing, validation techniques, and lineage.
  • Metadata Management: Curate rich metadata in Unity Catalog and Snowflake to power downstream consumption, including AI agents and our semantic layer (Cube.dev).
  • Research & Innovation: Research solutions to complex problems and lead proof-of-concepts to evaluate emerging technologies.
  • Documentation & Culture: Author and maintain high-quality documentation to support knowledge sharing and AI-assisted workflows.

What we're looking for

  • AI-Assisted Development: Strong understanding of AI-assisted development workflows, with proven hands-on experience using tools such as Cursor, Claude, OpenCode, GitHub Copilot, or ChatGPT to improve efficiency, automation, and code quality.
  • Spec-Driven Development: Experience with spec-driven development: turning requirements into clear specs/plans and acceptance criteria, then implementing them (including AI-agent-assisted workflows).
  • Snowflake Expertise (core skillset): 2+ years building and operating production data pipelines and models on Snowflake using SQL, Python, and dbt-shipping reliable ELT/transformations, owning quality and performance in production.
  • dbt Mastery: 2+ years of hands-on experience building modular, version-controlled, and tested data models using dbt (data build tool), treating transformation as software engineering (Git workflows, code review, automated tests).
  • AWS: 2+ years of experience with AWS cloud services.
  • Data Governance: A solid understanding of data quality, lineage, validation techniques, and data governance.
  • Collaboration & Communication: Ability to communicate complex technical concepts effectively to both technical and non-technical stakeholders, gather requirements, and work effectively in a distributed team.

Preferred / Additional Strengths

  • Databricks: Hands-on Databricks experience (workspaces, jobs/workflows, Spark SQL/PySpark, Delta Lake) to contribute to lakehouse work alongside Snowflake.
  • Managed Ingestion (Fivetran): Exposure to Fivetran (or similar ELT connectors) for reliable source-to-warehouse ingestion, connector governance, and schema-evolution handling.
  • Semantic Layer (Cube.dev): Exposure to Cube.dev (or a similar semantic/metrics layer) for governed, self-serve analytics and consistent metrics across products and consumers.
  • Real-Time Streaming: Strong preferred experience building and maintaining real-time data solutions using streaming platforms like Apache Kafka.

At AppDirect, we believe that innovation thrives in an environment that houses diversity of excellence, experience and thought. We respect each AppDirector as their own fingerprint; unique with no one alike. We foster an environment of inclusion without regard to race, religion, age, sexual orientation, or gender identity enabling AppDirectors to embrace their uniqueness to do their best work. As such, we strongly encourage applications from Indigenous peoples, racialized people, people with disabilities, people from gender and sexually diverse communities, and/or people with intersectional identities.

At AppDirect we take privacy very seriously. For more information about our use and handling of personal data from job applicants, please read our Candidate Privacy Policy. For more information of our general privacy practices, please see AppDirect Privacy Notice: 

https://www.appdirect.com/about/privacy-notice

At AppDirect, AI tools may assist our recruitment team with administrative automations - always under human oversight. AI tools do not make hiring decisions or solely automated decisions about your candidacy - all decisions are made by our people. By submitting your application, you acknowledge that your information may be processed in this way. You may request access or deletion at any time by contacting privacy@appdirect.com.

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