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Data Engineer Jobs in Saskatchewan (NOW HIRING)

Perform mechanical engineering design work on various projects executed within Cameco and act as Engineer of Record for issued drawings, specifications, data sheets, engineering lists and ...

Engineer Lead

Colonsay, SK

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Esterhazy K1 Are you our next Lead Engineer? The Mechanical Integrity Lead Structural Engineer ... Evaluate inspection data, degradation trends, and repair effectiveness; document residual risk and ...

Engineer Lead

Esterhazy, SK

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Esterhazy K1 Are you our next Lead Engineer? The Mechanical Integrity Lead Structural Engineer ... Evaluate inspection data, degradation trends, and repair effectiveness; document residual risk and ...

Engineer Lead

Regina, SK

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Esterhazy K1 Are you our next Lead Engineer? The Mechanical Integrity Lead Structural Engineer ... Evaluate inspection data, degradation trends, and repair effectiveness; document residual risk and ...

Engineer Lead

Belle Plaine, SK

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Esterhazy K1 Are you our next Lead Engineer? The Mechanical Integrity Lead Structural Engineer ... Evaluate inspection data, degradation trends, and repair effectiveness; document residual risk and ...

Your Impact The Forward Deployed Engineer is a front-line software engineer embedded directly in ... Design & build enterprise data integrations, RAG pipelines, and multi-system API workflows.

Engineering Location: Saskatoon, SK, Canada Join a company that is passionately committed to the ... Sound knowledge of 3D data-centric design systems. * Knowledge and experience with data-centric ...

In this role, you will be responsible for preparing engineering calculations, technical specifications, data sheets and reports, and assist/participate with on-site commissioning. The Role: * Assist ...

Junior Machine Learning Engineer

Saskatoon, SK · On-site

CA$80K - CA$95K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

You will work with data scientists, engineers, product teams, and business stakeholders to help transform ideas into scalable AI-enabled products and workflows. This role is well suited for someone ...

Manage documentation and data, and participate in quality assurance audits Skills / Qualifications * Minimum of 5 years engineering or operations experience focusing on heavy industrial projects ...

Mining Process Engineer

Regina, SK · Hybrid

CA$115K - CA$135K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Experience with APC, data analytics, historians, and data visualisation tools (asset); * PCB design ... Degree in Engineering or Computer Science (Electrical, Mechatronics, or related field); * 5+ years ...

Perform the design and produce drawings for building electrical systems (lighting, power, data, etc ... Must have Electrical Engineering degree * Must be licensed to practice as a Professional Engineer ...

Showing results 21-40

Data Engineer information

See Saskatchewan salary details

$60K

$122.6K

$181K

How much do data engineer jobs pay per year?

As of Aug 14, 2026, the average yearly pay for data engineer in Saskatchewan 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 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.

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.

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.

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.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior-level role that requires experience with programming, databases, and data pipelines. 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 and proficiency with tools like SQL, Python, and cloud platforms.

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

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

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

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

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

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

Infographic showing various Data Engineer job openings in Saskatchewan as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 22% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $122,622 per year, or $59 per hour.

Artificial Intelligence Systems Team Lead, Enterprise Architecture Data Management

American Institute for Chemical Engineers

Saskatoon, SK

Full-time

Posted 26 days ago


Job description

Summary:

The artificial intelligence (AI) systems team lead is responsible for leading the design, build, and deployment of institutional AI services that move from proof of concept into production within defined funding timelines. This role guides a technical team while shaping an AI systems roadmap that supports administrative automation, digital assistant capabilities, teaching and learning initiatives, and research computing. The team lead provides hands-on technical guidance while coordinating vendors, platforms, and institutional stakeholders to deliver operational AI services. The work focuses on producing measurable outcomes, including adoption, efficiency gains, and visible value from AI investment. 

Duties and Responsibilities:

  • Leads AI initiatives from concept to production, delivering measurable value through documented adoption and efficiency gains
  • Delivers and maintains an institutional AI services roadmap with defined milestones, adoption targets, and success criteria aligned to funding timelines
  • Provides overall technical architecture guidance for AI solutions, including integration patterns, security models, data flows, and platform selection
  • Oversees the development and maintenance of AI infrastructure, including model orchestration layers, governance workflows, API integrations, and protected computing environments
  • Establishes and operates secure AI environments (e.g., sandbox, pilot, and production) to support research, teaching, and administrative use cases
  • Leads vendor and tool evaluation, selection, and relationship management for AI platforms and services
  • Contributes technical perspective to institutional AI governance processes, risk assessments, and compliance reviews
  • Coordinates with internal teams and the broader unit to align AI initiatives with enterprise architecture, identity infrastructure, and integration standards
  • Engages with faculty, researchers, and administrative units to identify high-value AI opportunities and manage expectations
  • Reports on AI initiative outcomes, including adoption rates, integration health, user feedback, cost avoidance, and risk posture to senior leadership
  • Maintains the reliability, performance, and security of AI tools and digital assistant services through established engineering practices
  • Adopts and promotes responsible AI practices aligned with university policy, unit standards, and applicable regulatory requirements
  • Provides technical guidance, mentorship, and workflow planning for team members, and contributes to performance feedback processes as appropriate
  • Remains current with AI industry trends, emerging platforms, and leading practices, recommending enhancements aligned with institutional priorities
  • Communicates and acts in a respectful and professional manner, collaborates effectively, abides by policy, and contributes to a positive and productive work and learning environment
  • Engages in continuous learning byparticipatingin activities, training, and events related to Indigenous engagement, reconciliation, equity, diversity, and inclusion
  • Demonstrates respect and dignity for all members of the community, actively contributes to an environment of acceptance and inclusion of others, and responds to different perspectives from a place of curiosity, respect, and non-judgement
  • Undertakes related duties as assigned, consistent with the nature of the position

Qualifications:

  • A bachelor's degree in computer science, data science, engineering, or a related field
  • Minimum of five years of experience in enterprise application development, platform engineering, or systems integration, including experience with secure data pipelines, privacysensitive workloads, or research computing environments, as well as AI governance, model evaluation, risk assessment, and responsible AI practices
  • Experience providing leadership and mentorship to a team
  • Experience with AI and Machine Learning (ML) systems, cloud-based AI services, automation platforms, or intelligent workflow systems
  • Demonstrated experience delivering AI or automation solutions form proof of concept through production deployment
  • Ability to work effectively both independently and collaboratively in a team
  • Strong communication skills
  • Ability to translate institutional priorities into achievable AI-enabled solutions
  • Strong development skills in Python or Java with solid software engineering fundamentals is preferred
  • Proficiency with multi-agent or generative AI frameworks, AI vendor management, or higher education IT environments is an asset

Department: Department: Information and Communications Technology, Enterprise Architecture Data Management
Status:
Permanent
Employment Group: 
ASPA
Salary:
 The salary range, based on 1.0 FTE, is 87,266.00 - 145,353.00 per annum. The starting salary will be commensurate with education and experience.
Salary Family (if applicable): 
Information Technology
Salary Phase/Band: 
Phase 3
Posted Date:
 7/20/2026
Closing Date:
 8/31/2026 at 6:00 pm CST
Number of Openings: 
1
Work Location: May be eligible for hybrid work under the terms of USask's Alternative Workspace Guidelines

The successful applicant will be required to provide the following current verification where 'Yes' is indicated below. Further information is available at: Tips for Applying - Careers | University of Saskatchewan

Criminal Record Check: Yes
Driver's License and Abstract Check: Not Applicable
Education/Credential Verification: Not Applicable
Vulnerable Sector Check: Not Applicable

The University of Saskatchewan aspires to be what the world needs and embraces equity, diversity and inclusion as foundational to excellence and innovation. We actively seek to create a welcoming environment where all individuals feel empowered to thrive, contribute, and grow. Applications from equity-deserving groups are encouraged as part of our ongoing efforts to reflect the diversity of the communities we serve: EDI Framework for Action.
We continue to grow our partnerships with Indigenous communities across the province, nationally, and internationally and value the unique perspective that Indigenous employees provide to strengthen these relationships. Verification of Indigenous Membership/Citizenship at the University of Saskatchewan is led and determined by the deybwewin | taapwaywin | tapwewin: Indigenous Truth policy and the Standing Committee in accordance with the processes developed to enact the policy. Successful candidates that assert Indigenous membership/citizenship will be asked to complete the verification process of Indigenous membership/citizenship with documentation.
The University of Saskatchewan provides an accessible and inclusive workplace. Should you require support through any stage of the recruitment process, please contact us for assistance.