ZipRecruiter

Log In

1

Data Jobs in Saskatchewan (NOW HIRING)

Brandt

Data Architect

Regina, SK · On-site

As a Data Engineer, you will play a crucial role in developing and maintaining efficient data pipelines, ensuring data accuracy, and contributing to business intelligence initiatives. Duties and ...

Targeted Talent

Data Scientist

Saskatoon, SK · Remote

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+ ...

Targeted Talent

Data Scientist

Saskatoon, SK · Remote

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+ ...

Targeted Talent

Data Scientist

Saskatoon, SK · On-site

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 ...

Targeted Talent

Data Scientist

Saskatoon, SK · On-site

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 ...

Targeted Talent

Senior Data Scientist

Saskatoon, SK · Remote

We are looking for an experienced Senior 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 - ...

Targeted Talent

Senior Data Scientist

Saskatoon, SK · Remote

We are looking for an experienced Senior 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 - ...

KPMG

Data Support Senior Consultant

Regina, SK · On-site

The Central Data Support Team (CDST) is a part of the national audit center, audit support team. The CDST is tasked with implementing new technologies in the audit practice and providing digital and ...

TSMG

Data collector / Driver in Regina, SK

Regina, SK · On-site

We collect data where automation is not possible. We count features, take pictures, make videos, record speech, and scan areas for every detail you need to make more informed decisions. Our field ...

iQmetrix

Senior Data Engineer

Regina, SK · On-site

The Data & Analytics team is moving from a legacy reporting model to a modern data platform organization, one that powers embedded analytics, operational data products, and AI/ML capabilities across ...

Targeted Talent

Senior Data Engineer

Saskatoon, SK · Remote

We are looking for an experienced Senior Data Engineer for our client. This is a permanent position that is completely remote! Our client is a global enterprise company with a product that you've ...

next page

Showing results 1-20

All JobsData JobsData Jobs in Saskatchewan

Data information

What are different jobs that work with data?

Many different jobs require you to work with data. Occupational health and safety engineers, for instance, assess safety data collected by technicians and specialists and then design new processes to mitigate observed risks. Many careers in medical research, such as running clinical trials or developing new pharmaceuticals, require data collection and analysis. A large number of government labor and economic forecasting positions employ statisticians who analyze and model data based on surveys or raw information, such as the census or employment records.

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

To thrive as a Data Analyst, you need strong analytical skills, proficiency in statistics, and a solid foundation in mathematics, typically supported by a degree in a quantitative field. Familiarity with data analysis tools like Excel, SQL, Python, and visualization platforms such as Tableau or Power BI is often required, and certifications in these tools can be advantageous. Attention to detail, critical thinking, and effective communication skills help analysts interpret data accurately and present actionable insights to stakeholders. These skills are crucial for transforming raw data into meaningful information that drives informed business decisions.

How does a data analyst typically collaborate with other departments within an organization?

Data Analysts frequently work cross-functionally, partnering with teams such as marketing, finance, operations, and product development. They gather requirements from stakeholders, interpret data to provide actionable insights, and often present findings in meetings or reports tailored to the audience's needs. Effective communication is key, as analysts must translate complex data into clear, impactful recommendations that guide business decisions. This collaborative environment fosters both learning and professional growth, as Data Analysts gain exposure to various business functions.

What is the difference between Data vs Data Analyst?

AspectDataData Analyst
Required CredentialsTypically a degree in computer science, information technology, or related fieldsSame as Data, often requiring a degree in statistics, data science, or related areas
Work EnvironmentData professionals work in IT, data engineering, or database management settingsData analysts work in business, finance, marketing, and similar industries analyzing data for insights
Employer & Industry UsageUsed across tech, finance, healthcare, and more for data management and infrastructureCommonly employed in business sectors to interpret data and support decision-making

Data professionals focus on managing, storing, and processing data, while Data Analysts interpret and analyze data to generate insights. Both roles require similar educational backgrounds but differ in their primary functions within organizations.

What are careers in data?

Careers in data include roles such as data analyst, data scientist, data engineer, and database administrator. These jobs involve collecting, analyzing, and managing data using tools like SQL, Python, and data visualization software, often requiring strong analytical skills and knowledge of data management principles.

What data jobs are there?

Data jobs include roles such as data analyst, data scientist, data engineer, and database administrator. These positions typically require skills in programming, statistics, and data management tools like SQL, Python, or R, and may involve working with large datasets, data visualization, and machine learning techniques.
More about Data jobs

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 jobs in Saskatchewan look for?

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

Data jobs near you
Infographic showing various Data job openings in Saskatchewan as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 79% Physical, 3% Hybrid, and 18% Remote job distribution.

Data Architect

Brandt

Regina, SK • On-site

Full-time

Re-posted 19 days ago

Job description

 Brandt is seeking a highly skilled and motivated Data Engineer to join our dynamic team. The ideal candidate will have a strong background in designing, implementing, and optimizing data solutions using PowerBI, Azure, and AI technologies. As a Data Engineer, you will play a crucial role in developing and maintaining efficient data pipelines, ensuring data accuracy, and contributing to business intelligence initiatives.

Duties and Responsibilities 

Data Architecture & Strategy

  • Data Solution Design: Lead the architectural design, data modeling, and implementation of highly scalable data processing systems within the Azure Data ecosystem.
  • Strategic Advisement: Partner with senior management and internal stakeholders to define data strategies, establish benchmarks, and translate complex business requirements into robust technical specifications.
  • Enterprise Capability Advancement: Drive the maturity of our enterprise data stack, defining best practices for data organization, governance, and architecture.

 Data Engineering & Optimization

  • Advanced SQL & Performance Tuning: Act as the team's primary SQL authority. Proactively identify, troubleshoot, and optimize inefficient queries, fine-tune execution plans, and ensure optimal database performance.
  • ETL/ELT Pipeline Development: Architect and maintain robust, scalable data pipelines to extract, transform, and load data from disparate sources into Azure Data Factory and Azure Data Lake Storage.
  • Workflow Streamlining: Continuously monitor and optimize data workflows to reduce processing times, minimize compute costs, and improve overall system efficiency.

 Business Intelligence & Security

  • Data Security & Governance: Implement strict data security measures, including encryption, robust access controls, and data masking to safeguard sensitive enterprise information.
  • PowerBI & Analytics Integration: Architect the data models that feed PowerBI, enabling the creation of interactive, high-performance dashboards that provide actionable insights to stakeholders.

#LI-ONSITE 


Required Skills
  • Deep SQL Mastery: Expert-level proficiency in SQL (T-SQL preferred). Must have hands-on experience with query optimization, execution plan analysis, indexing strategies, complex joins, window functions, and CTEs.
  • Data Modeling: Strong background in relational and dimensional data modeling (Kimball/Inmon methodologies), data warehousing, and data dependencies across enterprise systems.
  • Azure Ecosystem: Deep expertise in Azure Data Factory, Azure SQL Database, and Azure Data Lake Storage.
  • Programming & BI: Highly proficient in Python and PowerBI (including DAX and Power Query optimization).
  • Emerging Tech: Familiarity with integrating machine learning models and AI tools into existing data workflows is a strong asset.

Required Experience
  • 5–10 years of proven experience in Data Architecture, with a heavy emphasis on Microsoft Azure technologies.
  • Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent enterprise experience).
  • Demonstrated ability to break down complex, ambiguous processes and explain highly technical concepts to non-technical senior leadership.

Apply