Jobs in Canada

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Added 9 days ago
Go-to-Market Engineer
OneRiver Software
Toronto, ON
We are seeking a technically minded, commercially driven Go-to-Market Engineer to build an AI-powered engine that identifies prospective customers, generates market interest, and creates a…
Added 9 days ago
Intermediate to Senior Autonomy Engineer
MACLEAN ENGINEERING & MARKETING CO. LIMITED
Barrie, ON
This is an onsite position 5 days per week and can be in our Barrie or Cambridge facilities
Added 9 days ago
RC
RQ07427 - SCADA Engineer
Randstad Canada
Burnaby, BC
- $55 to $75 CAD / hour
The E3 – Engineer is a fully qualified and accredited engineering professional who applies theoretical and practical knowledge to provide engineering design, estimating, planning, and…
Added 9 days ago
Senior Quality Engineer
Embross
Richmond Hill, ON
As a Quality Engineer, you are expected to ensure compliance with ISO 9001 & ISO 14001 standards across all processes, to conduct internal and supplier audits, inspections, and quality…
Added 9 days ago
Senior Machine Learning Engineer
Randstad Canada
Toronto, ON
We are seeking an experienced Senior Machine Learning Engineer to deploy, integrate, monitor, and operationalize enterprise AI and machine learning solutions using modern MLOps practices.…
Added 9 days ago
Senior Software Engineer
Third-Party Job Posts
Canada
As a 𝗦𝗲𝗻𝗶𝗼𝗿 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 on the Core AI Squad, you'll design, build, and operate customer-facing AI platform capabilities that power intelligent product…
Added 10 days ago
Senior Software Developer
Botpress Technologies Inc.
Montréal, QC
As a Senior Software Developer at Botpress, you’ll be at the forefront of developing innovative solutions that drive the future of conversational AI. As a senior member of the engineering…
Added 11 days ago
Quality Engineer (QE) / SDET – AI Chatbot Validation
Astra North Infoteck Inc.
Toronto, ON
We are looking for a seasoned AI first Senior Quality Engineer who is empowered to help the DevOps enablement team deliver highest level quality and is responsible for ensuring the team…
Added 11 days ago
Senior Staff Engineer, Software Defined Dataplane
Equinix (US) Enterprises, Inc.
Toronto, ON
We're looking for a Senior Staff Software Engineer who will be responsible for building easy to operate, reliable and high-performing applications and networking software for our next…
Added 12 days ago
Senior Tax & Audit AI Engineer, FDE
Thomson Reuters (Tax & Accounting) Inc
Toronto, ON
Partner with public accounting firms and corporate tax departments to understand workflows, identify automation opportunities and define successful outcomes.
Added 14 days ago
Senior Quality Engineer
Takeaway
Winnipeg, MB · Edmonton, AB
As a Senior Quality Engineer, you will work with an elite team of developers to build scalable systems and troubleshoot using various tools.
Added 15 days ago
S
Senior AI Security Automation Engineer
SSB&T
Toronto, ON
- $120,000 to $202,500 CAD / year
State Street's Cyber Data & Analytics (CyberDNA) team is seeking a Senior AI Security Automation Engineer to help shape the next generation of cybersecurity data, analytics, and AI-powered…
Added 15 days ago
Manufacturing Engineer
Norsat International Inc.
Aurora, ON
The Manufacturing Engineer is responsible for developing, implementing, supporting, and continuously improving manufacturing processes for RF antennas, filters, combiners, and related…
Added 16 days ago
Senior Backend Software Engineer - Kalepa for Operations
Kalepa
Canada
…the insights insurers rely on for high-stakes decisions. As a Senior Backend Engineer, you'll own strategically important, complex pieces of that system with minimal oversight: the…
Added 16 days ago
Software Developer .net
Futuretek
Toronto, ON
Delivery & Ownership - must have:
Added 17 days ago
E
EverCommerce - Staff Engineer
Evercommerce
ON
- $160,000 to $190,000 CAD / year
…event-driven Java/Spring Boot microservice in the morning, mentor a senior engineer on system design in the afternoon, and deploy generative AI / agentic workflows (AWS Bedrock) to…
Added 17 days ago
IG
QE Lead, Functional
Insight Global
Vancouver, BC
- $113,000 to $140,000 CAD / year
senior technical role responsible for ensuring the quality, reliability, and performance of member-facing platforms through hands-on engineering leadership and execution of automation-first…
Added 17 days ago
Staff Software Engineer (Applied AI)
GuruLink
Toronto, ON
Must Have Skills:
Added 17 days ago
P
Quality Engineering Architect
Procom
Mississauga, ON
- $60 to $80 CAD / hour
We are seeking a visionary and hands-on Senior Software Development Engineer in Test (SDET) / Quality Engineering Architect to define, champion, and drive the global quality engineering…
Added 17 days ago
Senior Mechanical Engineer
Rockford Engineering Works Ltd.
Regina, SK
The Senior Mechanical Engineer leads complex projects from acquisition to completion, mentors team members, and represents Rockford in client engagements. The ideal candidate combines…
Added 18 days ago
I
AI Integration Developer
IntuitionLabs
Remote, Canada
- $80,000 to $100,000 CAD / year
Mentoring from a senior engineer and direct work with the founder
Added 18 days ago
Automation & Manual QA Engineer
Querentia Inc.
Remote, Canada
The ideal candidate must have extensive hands-on expertise in C# test automation , API testing , and Postman
Added 18 days ago
RC
Software Developer IV
Randstad Canada
Toronto, ON
- $55.68 to $65.51 CAD / hour
If you are a tech-savvy Software Developer IV / Senior Quality Engineer who pairs strong programming skills in Java, JavaScript, or Python with deep API test automation mastery, Playwright…
Added 21 days ago
Ingénieur principal de projet – HVDC/Senior Project Lead Engineer HVDC
Hitachi Global
Montréal, QC
Hitachi Energy's Grid Automation business is seeking a Senior Project Lead Engineer to take technical ownership of complex HVDC projects and tenders. In this role, you will coordinate…
Added 21 days ago
Ingénieur principal de projet – HVDC/Senior Project Lead Engineer HVDC
HITACHI ENERGY USA INC
Saint-Laurent, QC
Hitachi Energy's Grid Automation business is seeking a Senior Project Lead Engineer to take technical ownership of complex HVDC projects and tenders. In this role, you will coordinate…

Autodesk

Data Engineer

Toronto, ON, Canada

$88,000 to $128,700 CAD / year

Apply on jobs.autodesk.com About employer

Applications open in a new tab.

Job details

Pay: $88,000 to $128,700 CAD / year
Apply by: May 8, 2027
Posting language: English · French
Posted: Nov 9, 2026

Original job description

English section of this bilingual listing.

Job Requisition ID #

26WD101542

Position Overview

Autodesk is looking for a skilled and innovative Senior Data Engineer to join our Compliance team, which builds data-driven systems to detect and address non-compliant usage of Autodesk software. This is a key strategic initiative that leverages large-scale data processing and analytics to drive business impact.

In this role, you will design, build, and optimize scalable data pipelines and distributed processing systems that handle billions of records. You will focus on improving platform reliability, performance, scalability, and operational efficiency while enabling business-critical analytics.

We are looking for an engineer who combines strong expertise in big data technologies with hands-on experience using AI-powered development tools to accelerate engineering workflows, improve code quality, and deliver solutions faster.

The ideal candidate is technically strong, self-driven, comfortable owning complex engineering initiatives, and passionate about leveraging modern technologies and AI-assisted development practices to solve challenging data engineering problems.

Our technology stack includes: Python, SQL, Apache Spark, PySpark, Spark SQL, Apache Airflow, Hive, Presto/Trino, Snowflake, AWS (S3, EMR, Glue), Git, Jenkins, Power BI, Looker, and AI-assisted development tools such as GitHub Copilot, Cursor, ChatGPT, Claude, or equivalent solutions.

Responsibilities

Leverage AI-powered development tools to accelerate coding, debugging, refactoring, test generation, documentation, and troubleshooting of complex data engineering solutions
Integrate AI-assisted development practices into engineering workflows to improve productivity, code quality, and delivery speed
Evaluate and validate AI-generated solutions for correctness, performance, maintainability, and security while following responsible AI practices
Identify opportunities to automate repetitive engineering tasks and improve developer efficiency through AI-powered solutions
Design, develop, and optimize large-scale batch and near-real-time data processing pipelines using Apache Spark, PySpark, and Spark SQL
Build scalable and efficient ETL/ELT pipelines capable of processing billions of records across distributed data platforms
Optimize distributed processing workloads through partitioning, efficient joins, query tuning, resource management, and performance analysis
Develop and maintain data processing solutions using technologies such as Hive, Snowflake, AWS S3, EMR, and Glue
Build and maintain production-grade data workflows using Apache Airflow, including DAG development, scheduling, dependency management, retries, and failure recovery
Implement data quality checks, pipeline monitoring, observability, and alerting to ensure reliable data processing
Design reusable, modular, and fault-tolerant pipelines supporting incremental processing, backfills, and operational scalability
Troubleshoot production issues and continuously improve pipeline reliability, performance, and cost efficiency
Develop and maintain scalable, cloud-native data infrastructure on AWS
Automate infrastructure provisioning, deployments, and operational processes using Infrastructure as Code and CI/CD practices
Implement automated testing, version control, code reviews, and software engineering best practices
Own the end-to-end delivery of data engineering solutions, from technical design and implementation to deployment and production support
Partner with product managers, data scientists, analysts, and business stakeholders to translate business requirements into scalable technical solutions
Design efficient data models and curated datasets to support compliance detection, product usage analytics, and business reporting
Define and promote data engineering standards, reusable frameworks, and architectural best practices
Communicate technical designs, trade-offs, and engineering outcomes effectively to stakeholders

Minimum Qualifications

4–7 years of relevant experience in data engineering, big data systems, or software engineering, building and operating production-grade data platforms
3+ years of hands-on experience with Apache Spark, including PySpark, Spark SQL, and DataFrame APIs
3+ years of strong programming experience in Python and SQL, with demonstrated ability to write clean, modular, maintainable, and testable code
Strong understanding of distributed computing fundamentals, including parallel processing, partitioning, shuffling, data skew, fault tolerance, and Spark performance tuning
Hands-on experience with Apache Airflow for building, scheduling, and orchestrating complex data pipelines
Strong knowledge of ETL/ELT design patterns, data modeling, SQL optimization, and large-scale data processing architectures
Practical experience using AI-powered coding tools such as GitHub Copilot, Cursor, ChatGPT, Claude, or equivalent solutions in day-to-day software or data engineering development
Ability to effectively use AI tools for code generation, debugging, refactoring, testing, and accelerating engineering problem-solving
Understanding of AI-assisted development best practices, including prompt formulation, code validation, secure usage, and identifying limitations of AI-generated solutions
Experience with AWS data services such as S3, EMR, Glue, or equivalent cloud-based data processing platforms
Working knowledge of analytical data platforms such as Snowflake, Hive, or Presto/Trino
Experience with Git, CI/CD pipelines, and automation tools such as Jenkins
Familiarity with data quality frameworks, pipeline observability, production monitoring, and troubleshooting
Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience

Preferred Qualifications

Experience with modern data lake or lakehouse architectures, including Apache Iceberg, Delta Lake, or Apache Hudi
Familiarity with streaming data processing technologies such as Apache Kafka or Spark Structured Streaming
Experience with Infrastructure as Code tools such as Terraform or AWS CloudFormation
Experience developing reusable data engineering frameworks, libraries, or internal developer productivity tools
Familiarity with LLM APIs, AI agents, or AI-powered workflow automation applied to software or data engineering
Experience with BI and analytics platforms such as Power BI or Looker
Demonstrated experience improving engineering efficiency, pipeline performance, or cloud infrastructure costs through automation and optimization

Learn More / En savoir plus

About Autodesk

Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.

We take great pride in our culture here at Autodesk – it’s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.

When you’re an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!

À propos d’Autodesk

Belonging / appurtenance
We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/global-belonging

This role may require in-person onboarding and/or in-person ID verification.

Read the full bilingual original

Job Requisition ID #

26WD101542

Position Overview

Responsibilities

Leverage AI-powered development tools to accelerate coding, debugging, refactoring, test generation, documentation, and troubleshooting of complex data engineering solutions
Integrate AI-assisted development practices into engineering workflows to improve productivity, code quality, and delivery speed
Evaluate and validate AI-generated solutions for correctness, performance, maintainability, and security while following responsible AI practices
Identify opportunities to automate repetitive engineering tasks and improve developer efficiency through AI-powered solutions
Design, develop, and optimize large-scale batch and near-real-time data processing pipelines using Apache Spark, PySpark, and Spark SQL
Build scalable and efficient ETL/ELT pipelines capable of processing billions of records across distributed data platforms
Optimize distributed processing workloads through partitioning, efficient joins, query tuning, resource management, and performance analysis
Develop and maintain data processing solutions using technologies such as Hive, Snowflake, AWS S3, EMR, and Glue
Build and maintain production-grade data workflows using Apache Airflow, including DAG development, scheduling, dependency management, retries, and failure recovery
Implement data quality checks, pipeline monitoring, observability, and alerting to ensure reliable data processing
Design reusable, modular, and fault-tolerant pipelines supporting incremental processing, backfills, and operational scalability
Troubleshoot production issues and continuously improve pipeline reliability, performance, and cost efficiency
Develop and maintain scalable, cloud-native data infrastructure on AWS
Automate infrastructure provisioning, deployments, and operational processes using Infrastructure as Code and CI/CD practices
Implement automated testing, version control, code reviews, and software engineering best practices
Own the end-to-end delivery of data engineering solutions, from technical design and implementation to deployment and production support
Partner with product managers, data scientists, analysts, and business stakeholders to translate business requirements into scalable technical solutions
Design efficient data models and curated datasets to support compliance detection, product usage analytics, and business reporting
Define and promote data engineering standards, reusable frameworks, and architectural best practices
Communicate technical designs, trade-offs, and engineering outcomes effectively to stakeholders

Minimum Qualifications

4–7 years of relevant experience in data engineering, big data systems, or software engineering, building and operating production-grade data platforms
3+ years of hands-on experience with Apache Spark, including PySpark, Spark SQL, and DataFrame APIs
3+ years of strong programming experience in Python and SQL, with demonstrated ability to write clean, modular, maintainable, and testable code
Strong understanding of distributed computing fundamentals, including parallel processing, partitioning, shuffling, data skew, fault tolerance, and Spark performance tuning
Hands-on experience with Apache Airflow for building, scheduling, and orchestrating complex data pipelines
Strong knowledge of ETL/ELT design patterns, data modeling, SQL optimization, and large-scale data processing architectures
Practical experience using AI-powered coding tools such as GitHub Copilot, Cursor, ChatGPT, Claude, or equivalent solutions in day-to-day software or data engineering development
Ability to effectively use AI tools for code generation, debugging, refactoring, testing, and accelerating engineering problem-solving
Understanding of AI-assisted development best practices, including prompt formulation, code validation, secure usage, and identifying limitations of AI-generated solutions
Experience with AWS data services such as S3, EMR, Glue, or equivalent cloud-based data processing platforms
Working knowledge of analytical data platforms such as Snowflake, Hive, or Presto/Trino
Experience with Git, CI/CD pipelines, and automation tools such as Jenkins
Familiarity with data quality frameworks, pipeline observability, production monitoring, and troubleshooting
Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience

Preferred Qualifications

Experience with modern data lake or lakehouse architectures, including Apache Iceberg, Delta Lake, or Apache Hudi
Familiarity with streaming data processing technologies such as Apache Kafka or Spark Structured Streaming
Experience with Infrastructure as Code tools such as Terraform or AWS CloudFormation
Experience developing reusable data engineering frameworks, libraries, or internal developer productivity tools
Familiarity with LLM APIs, AI agents, or AI-powered workflow automation applied to software or data engineering
Experience with BI and analytics platforms such as Power BI or Looker
Demonstrated experience improving engineering efficiency, pipeline performance, or cloud infrastructure costs through automation and optimization

Learn More / En savoir plus

About Autodesk

When you’re an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!

À propos d’Autodesk

Bienvenue chez Autodesk ! Nos logiciels créent chaque jour des choses extraordinaires : des bâtiments les plus écologiques aux voitures les plus propres, en passant par les usines les plus intelligentes et les films à succès. Nous aidons les innovateurs à concrétiser leurs idées, transformant non seulement la façon dont les choses sont fabriquées, mais aussi ce qui peut l’être.

Nous sommes très fiers de notre culture chez Autodesk ; elle est au cœur de tout ce que nous faisons. Notre culture guide notre façon de travailler et de nous comporter les uns envers les autres, influence nos interactions avec nos clients et nos partenaires, et définit notre image au monde.

En tant qu’Autodeskien, vous pouvez accomplir un travail significatif qui contribue à bâtir un monde meilleur, conçu et réalisé pour tous. Prêt à façonner le monde et votre avenir ? Rejoignez-nous !

Salary transparency / Transparence Salariale

Salary is one part of Autodesk’s competitive compensation package. For Canada based roles, we expect a starting base salary between $88,000 and $128,700 Annual. Offers are based on the candidate’s experience and geographic location, and may exceed this range. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package. Le salaire est l'un des éléments du programme de rémunération concurrentiel d'Autodesk. Pour les postes basés au Canada, nous offrons un salaire de base entre $88,000 et $128,700 annuel. Le salaire est déterminé selon l'expérience professionnelle et l'emplacement du candidat(e), et peut dépasser cette fourchette. En plus du salaire de base, notre programme de rémunération peut inclure une prime annuelle, des commissions pour les postes de ventes, des attributions d'actions et un ensemble complet d'avantages sociaux.

Belonging / appurtenance
We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/global-belonging

Nous sommes fiers de cultiver une culture d’appartenance où chacun peut s’épanouir. Pour en savoir plus, cliquez ici: https://www.autodesk.com/company/global-belonging

In-Person Onboarding and Identity Verification

Intégration en présentiel et vérification d’identité

This role may require in-person onboarding and/or in-person ID verification.

Ce poste peut nécessiter une intégration et/ou une vérification d'identité en présentiel.

Apply on jobs.autodesk.com About employer

More about this job

Responsibilities

The Senior Data Engineer at Autodesk will design and maintain large data pipelines that process billions of records, keep them reliable and fast, and use AI tools to speed up coding and testing. The role also works with product, analytics and business teams to turn requirements into data solutions.

Requirements

Candidates need 4-7 years of data engineering experience, including 3+ years with Apache Spark and 3+ years of Python and SQL. They also need hands-on Airflow experience, AWS data services and familiarity with AI-powered coding tools.

Skills

Apache Spark
PySpark
Spark SQL
DataFrame APIs
Apache Airflow
Python
SQL
Hive
Presto/Trino
Snowflake
AWS S3
AWS EMR
AWS Glue
Git
Jenkins
CI/CD
GitHub Copilot
Cursor
ChatGPT
Claude
Power BI
Looker
Distributed computing
Data modeling
ETL/ELT design

Benefits

Annual cash bonus
Stock grants

Keywords

Senior Data Engineer
Apache Spark
PySpark
Spark SQL
Apache Airflow
Python
SQL
Hive
Presto
Trino
Snowflake
AWS
S3
EMR
Glue
ETL
ELT
data pipelines
AI-assisted development
GitHub Copilot

Seniority

Senior

Perks

Performance bonus
Stock or equity

Tools

Apache Spark
PySpark
Apache Airflow
Snowflake
AWS S3
AWS EMR
AWS Glue
Hive
Presto/Trino
Git

Languages

English
French

Fields of study

Computer Science
Engineering

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Work requirements

Jobs in Canada