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Data Management Jobs in Saskatchewan (NOW HIRING)

Manager, Data Operations

Regina, SK · On-site

CA$109K - CA$145K/yr

Service Management & Operations Excellence * Leads and matures IT Service Management (ITSM) practices as they relate to data platforms and analytics services. * Ensures monitoring, alerting, and ...

$29.95 - $35.04/hr

Certificate, diploma, or post-secondary education in Office Administration, Business Administration, Data Management, Human Services, or a related field. * Equivalent combination of education ...

General AccountabilityThe Survey & Data Officer will work closely with the Data Analyst Manager and First Nation networks, government, and other stakeholders to help ensure the goals and objectives ...

Partner with senior management and internal stakeholders to define data strategies, establish benchmarks, and translate complex business requirements into robust technical specifications.

Manager - Hydrogeology

Saskatoon, SK · On-site +1

CA$120K - CA$180K/yr

Responsible for implementation of data quality processes for hydrogeology projects, including appropriate data management, review and storage. * Interface with other technical experts to achieve ...

As a federal Crown corporation, we provide financing, knowledge resources and business management ... As a Senior Data Scientist,you'lllead complex analytics initiatives,determinetechnical approaches ...

New

US HQ (hybrid) About Rubrik Rubrik is one of the fastest-growing companies in Silicon Valley, revolutionizing data protection and management in the emerging multi-cloud world. We are a one-of-a-kind ...

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Data Management information

See Saskatchewan salary details

$13

$31

$63

How much do data management jobs pay per hour?

As of Aug 8, 2026, the average hourly pay for data management in Saskatchewan is $31.46, according to ZipRecruiter salary data. Most workers in this role earn between $18.03 and $50.00 per hour, depending on experience, location, and employer.

What are some common challenges faced by data management professionals in ensuring data quality and consistency across departments?

Data Management professionals often encounter challenges such as inconsistent data entry practices, siloed information systems, and varying data standards across departments. Addressing these issues typically involves implementing data governance frameworks, standardizing processes, and fostering collaboration between teams to ensure data integrity. Regular audits, cross-functional meetings, and the use of data quality tools are common strategies employed to maintain high standards and support organizational decision-making.

What is a data management analyst?

A data management analyst is responsible for maintaining databases. In this position, your responsibilities are to keep an eye on how secure the data is and look for ways to increase user efficiency when accessing it. For example, you might move the database to an online cloud-based server to free up system resources. A data management analyst has to have a solid grasp of network technology, in addition to familiarity with database and spreadsheet software, to perform the duties of the job.

What are the key skills and qualifications needed to thrive in data management, and why are they important?

To excel in Data Management, you need a strong background in data analysis, database design, and data governance, often supported by a degree in computer science or information systems. Familiarity with database management systems (like SQL, Oracle), data visualization tools, and certifications such as Certified Data Management Professional (CDMP) are highly valued. Attention to detail, problem-solving, and strong organizational skills help professionals ensure data integrity and facilitate effective collaboration. These competencies are crucial for maintaining accurate, secure, and accessible data, which underpins informed business decision-making.

What skills are needed for data management?

Data management professionals need strong analytical skills, attention to detail, and proficiency with database tools such as SQL and Excel. Knowledge of data governance, data quality, and familiarity with data management software are also important for effective data organization and security.

What is data management as a job?

Data management as a job involves organizing, storing, and maintaining data to ensure its accuracy, security, and accessibility. Professionals in this field often work with database tools, data governance policies, and data quality standards to support business operations and decision-making.

What is data management?

Data management is the process of collecting, storing, organizing, and maintaining data in a secure and efficient manner. It ensures that data is accurate, available, and accessible to authorized users when needed. Good data management practices help organizations make informed decisions, comply with regulations, and protect sensitive information. It often involves the use of specialized software, policies, and procedures to handle data throughout its lifecycle.

What is the difference between Data Management vs Data Analyst?

AspectData ManagementData Analyst
Primary FocusOrganizing, storing, and maintaining data integrityAnalyzing data to extract insights and support decision-making
Skills & CertificationsDatabase management, SQL, data governance certificationsStatistical analysis, Excel, data visualization tools
Work EnvironmentData warehouses, IT departments, enterprise systemsBusiness units, analytics teams, consulting firms
Industry UsageUsed across industries for data infrastructureUsed for reporting, forecasting, and strategic analysis

While Data Management focuses on maintaining and organizing data infrastructure, Data Analysts interpret this data to generate insights. Both roles are essential for effective data-driven decision-making but serve different functions within an organization.

What are the most commonly searched types of Data Management jobs in Saskatchewan? The most popular types of Data Management jobs in Saskatchewan are:
Infographic showing various Data Management job openings in Saskatchewan as of August 2026, with employment types broken down into 84% Full Time, 13% Part Time, 1% Temporary, and 2% Contract. Highlights an 80% Physical, 2% Hybrid, and 18% Remote job distribution, with an average salary of $65,442 per year, or $31.5 per hour.

Artificial Intelligence Systems Team Lead, Enterprise Architecture Data Management

University of Saskatchewan

Saskatoon, SK

Full-time

Posted 20 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.