1

Data Manager Jobs in Saskatchewan (NOW HIRING)

$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 ...

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

We are looking for an experienced Data Scientist for our client. This is a permanent position that is completely remote! Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ ...

We are looking for an experienced Data Scientist for our client. This is a permanent position that is completely remote! Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ ...

We are looking for a Junior to Intermediate Data Scientist for our client. This is a permanent position that is remote to start with later relocation to Calgary or Winnipeg . Our client is a global ...

We are looking for a Junior to Intermediate Data Scientist for our client. This is a permanent position that is remote to start with later relocation to Calgary or Winnipeg . Our client is a global ...

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 ...

Comfortable managing diverse responsibilities from day to day administrative and operational work to project and deadline driven tasks * Resourceful and creative problem-solving skills- you are ...

next page

Showing results 1-20

Data Manager information

See Saskatchewan salary details

$26.5K

$86.1K

$197K

How much do data manager jobs pay per year?

As of Aug 29, 2026, the average yearly pay for data manager in Saskatchewan is $86,113.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,000.00 and $100,000.00 per year, depending on experience, location, and employer.

How does a data manager typically collaborate with other departments to ensure data integrity?

As a Data Manager, collaboration with various departments—such as IT, analytics, and operations—is essential to maintain data integrity and consistency. You’ll regularly coordinate with these teams to establish data governance protocols, resolve discrepancies, and ensure that data collection and storage meet organizational standards. Open communication and regular meetings help address data quality issues and align data management practices across the organization. This cross-functional work not only supports accurate reporting but also drives better decision-making company-wide.

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

To thrive as a Data Manager, you need expertise in data management principles, database administration, and data governance, often supported by a bachelor's degree in computer science or a related field. Familiarity with SQL, data warehousing tools, data visualization platforms, and certifications like CDMP or DAMA are typically required. Strong analytical thinking, attention to detail, and effective communication are essential soft skills for ensuring data integrity and collaborating with stakeholders. These skills and qualifications are crucial for maintaining secure, accurate data systems and supporting informed business decisions.

What is the difference between Data Manager vs Data Analyst?

AspectData ManagerData Analyst
Required CredentialsBachelor's degree in IT, Computer Science, or related field; certifications like CDMP or DAMA often preferredBachelor's degree in Statistics, Mathematics, or related field; certifications like CAP or Microsoft Data Analyst are common
Work EnvironmentTypically manages data systems, databases, and teams; works in IT or data departmentsAnalyzes data sets, creates reports, and visualizations; often works in business or analytics teams
Employer & Industry UsageUsed across industries like healthcare, finance, and tech for data governance and managementCommon in marketing, finance, and consulting for insights and decision-making

While both roles involve working with data, Data Managers focus on overseeing data systems and ensuring data quality, whereas Data Analysts interpret data to generate insights. Understanding these differences helps in choosing the right career path or job search focus.

Are data managers in demand?

Data managers are in high demand across various industries due to the increasing reliance on data-driven decision making. They typically require strong skills in database management, data analysis, and familiarity with tools like SQL and data visualization software, making their role essential for organizations managing large data sets.

What is the role of a data manager?

A data manager is responsible for overseeing the collection, storage, organization, and maintenance of data within an organization. They ensure data quality, security, and accessibility, often using database management tools and following data governance standards. Their role supports data analysis and decision-making processes.

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

The most popular types of Data jobs in Saskatchewan are:

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

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

What cities in Saskatchewan are hiring for Data Manager jobs?

Cities in Saskatchewan with the most Data Manager job openings:

Infographic showing various Data Manager job openings in Saskatchewan as of August 2026, with employment types broken down into 87% Full Time, 12% Part Time, and 1% Contract. Highlights an 75% Physical, 2% Hybrid, and 23% Remote job distribution, with an average salary of $86,113 per year, or $41.4 per hour.

Data Engineer (3 temporary full-time positions available)

Regina, SK • On-site

Full-time, Temporary

This job post has expired today. Applications are no longer accepted.


Job description

At GMS, we've been helping Canadians for more than 75 years to get the health and travel insurance they want and need. The same pioneering spirit that started our story is what drives us to do things differently today. Insurance, honestly, is our promise, and it's what we do at GMS. We care about our customers, our community and each other. As a non-profit organization, we're proud to reinvest our profits into the health of the communities we serve and that have supported us since 1949.We want our employees to feel good about coming to work and being in a workplace that promotes flexibility, growth and a healthy work-life balance. If you'd like to be part of a team that truly takes care of our customers, our communities, and each other, this could be your chance.Here's the roleThe Data Engineer is responsible for building and maintaining data integration services in GMS's data platform. This role will also be heavily involved in developing database architectures and data models that are utilized in GMS's information management services. This role will apply database best practices to automate data flow processes and support designing a scalable and reliable data management platform. To be successful, the Data Engineer will be conducting research and documenting data requirements that are leveraged in building data collection processes from various sources such as Azure Storage services and SQL databases. The Data Engineer plays a key role in developing and implementing data administration and governance policies and standards, and data modeling essentials for GMS's Extract-Transform-Load (ETL) process. Furthermore, this role is responsible for writing SQL scripts, building stored procedures and triggers and operating database management systems.Position Responsibilities•Research and document data requirements and data collection processes.•Collect and document GMS's user requirements for data storage services.•Develop and implement data administration policy, standards and data models that need to be applied to ETL process.•Apply best practices to data cleansing and validation steps in data pipelines.•Collect data from different sources such as GMS SQL databases.•Conduct research and provide advice to other information systems professionals and business SMEs regarding the collection, availability, security, and suitability of GMS data.•Support designing and implementing data integration services between GMS's core Cloud infrastructure and third-party vendors.•Write scripts related to stored procedures and triggers in GMS's Cloud SQL Database.•Develop database architecture for information systems projects.•Modify GMS's data models and database management systems on Azure to improve efficiency.•Identify and implement internal process improvements such as automating manual data processes and optimizing data delivery.•Export data from database management systems to perform data mining analysis.•Collaborate with the Data team to build strategies around data management and lifecycle.•Build, and test data pipelines and ETL processes from a wide variety of data sources including structured, semi-structured and unstructured data, using Azure Data tools such as Azure Data Factory, Azure SQL, Microsoft Fabric and more.•Maintain GMS's data pipelines and expand them according to the new requirements due to business growth.•Research and explore ways to enhance data quality, reliability, and efficiency.•Identify and evaluate methods and technology solutions to improve data flows.•Work with business stakeholders to assist with data-related technical issues and support their data infrastructure needs.Competencies•Impact and Influence: Uses active listening skills to understand a perspective and opinion; respectfully considers a different perspective; shares opinions and thoughts openly regardless of a shared or counter opinion.•Quality Orientation: Completes tasks with a high level of accuracy; routinely checks inputs, outputs, tasks, and processes to ensure they are error free. •Critical Thinking: Uses data and experience to understand and develop solutions to a range of business problems; validates inputs, assumptions, and outputs for reasonableness; sees connections between actions and their consequences.•Problem Solving: Actively explores and analyzes options and solutions to make effective customer and business decisions; considers causal relationships and impacts of risk decisions within area of knowledge and expertise.Education & Experience•Post-secondary education in Computer Science, Software Engineering, Statistics, or equivalent combination of education and experience.•3+ years' experience of developing and maintaining ETL and data pipelines.•Highly proficient in SQL, Azure Data Factory, and Database Management Systems.•Proficient in working with structured, semi-structured and unstructured data.•Advanced experience working with relational databases as well as familiarity with non-relational databases.•A successful history of extracting, manipulating, processing, and analyzing data from multiple disconnected datasets.•Experience performing root cause analysis on data processes and ETLs to answer specific business questions, troubleshoot issues and identify opportunities for improvement.•Experience with Azure data storage and processing services.Are we a fit?If you think so, please apply by August 28, 2026. We'd love to reach out to everyone who applies, but we just don't have enough hands! If you're selected for an interview, we'll be in touch. If not, please consider us again in the future.