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Data Engineering Jobs in Saskatchewan (NOW HIRING)

Brandt

Data Architect

Regina, SK

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

Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong ...

Targeted Talent

Data Scientist

Saskatoon, SK · Remote

Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong ...

Targeted Talent

Senior Data Scientist

Saskatoon, SK · Remote

Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong ...

Targeted Talent

Senior Data Scientist

Saskatoon, SK · Remote

Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong ...

Conexus Credit Union

Data Engineer

Regina, SK · On-site

CA$93K - CA$134K/yr

Automating and optimizing data ingestion, transformation, and deployment processes using modern engineering practices. * Monitoring platform performance and implementing data quality controls to ...

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 ...

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 ...

Targeted Talent

Junior Data Engineer

Saskatoon, SK · On-site

We are looking for an experienced Junior Data Engineer 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

Junior Data Engineer

Saskatoon, SK · On-site

We are looking for an experienced Junior Data Engineer 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

R Developer

Saskatoon, SK · Remote

Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong ...

Targeted Talent

R Developer

Saskatoon, SK · Remote

Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong ...

iQmetrix

Senior Data Engineer

Regina, SK · On-site

That means building high-quality lakehouse pipelines, enforcing rigorous data quality standards, and creating engineering patterns that let analytics, product, engineering, and AI initiatives move ...

Targeted Talent

Senior Database Developer

Saskatoon, SK · Remote

$95K - $110K/yr

We are looking for an experienced Data Developer for our client. This is a permanent position, remote! Our client is a large fintech firm with a product that you've likely used many times before. You ...

Targeted Talent

Senior Database Developer

Saskatoon, SK · Remote

$95K - $110K/yr

We are looking for an experienced Data Developer for our client. This is a permanent position, remote! Our client is a large fintech firm with a product that you've likely used many times before. You ...

Conexus Credit Union

Data Scientist

Regina, SK · On-site

CA$86K - CA$123K/yr

Post secondary education in Computer Science, Engineering, Mathematics, Statistics, a related discipline, or equivalent professional experience * 4-7+ years of experience delivering data science ...

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All JobsData Engineering JobsData Engineering Jobs in Saskatchewan

Data Engineering information

See Saskatchewan salary details

$25K

$135.7K

$228.5K

How much do data engineering jobs pay per year?

As of Jul 27, 2026, the average yearly pay for data engineering in Saskatchewan is $135,712.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,500.00 and $172,000.00 per year, depending on experience, location, and employer.

Is AI replacing data engineers?

AI is automating certain tasks within data engineering, such as data cleaning and pipeline management, but it does not replace the need for data engineers. Data engineers are essential for designing, building, and maintaining complex data systems, and their expertise in tools like SQL, Spark, and cloud platforms remains critical for managing data workflows and ensuring data quality.

What work does a data engineer do?

A data engineer designs, builds, and maintains data pipelines and infrastructure to collect, store, and process large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible, reliable, and optimized for analysis by data scientists and analysts.

What are the typical daily responsibilities of a Data Engineer?

Data Engineers regularly design, build, and maintain scalable data pipelines to support analytics and business intelligence teams. Their daily tasks often involve working with large datasets, optimizing data storage, ensuring data integrity, and troubleshooting data-related issues. Collaboration with data scientists, analysts, and software engineers is common to align on data requirements and improve workflows. You may also participate in regular code reviews and contribute to the ongoing improvement of data infrastructure. This role is ideal for problem-solvers who enjoy working with both code and complex systems in a collaborative, fast-paced environment.

What engineers make 500,000?

Senior data engineers with extensive experience, specialized skills in cloud platforms, and advanced knowledge of data architecture can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires a combination of technical expertise, leadership roles, and sometimes stock options or bonuses.

What is a Data Engineering job?

A Data Engineering job involves designing, building, and maintaining the infrastructure that enables efficient data collection, storage, and processing. Data Engineers develop pipelines to transform raw data into usable formats for analytics and machine learning. They work with databases, big data technologies, and cloud platforms to ensure data is accessible and reliable. Their role is crucial for organizations to make data-driven decisions and optimize business processes.

Are data engineers still in demand?

Data engineers are currently in high demand due to the increasing reliance on data-driven decision making and the growth of big data technologies. They typically require skills in SQL, cloud platforms, and data pipeline tools like Apache Spark or Kafka, making their expertise valuable across many industries. The role is expected to remain strong as organizations continue to prioritize data infrastructure and analytics capabilities.

What are the key skills and qualifications needed to thrive in the Data Engineering position, and why are they important?

To thrive in Data Engineering, you need a solid background in programming (such as Python, Java, or Scala), data modeling, and database management, typically supported by a degree in computer science or a related field. Familiarity with ETL tools, cloud platforms like AWS or Azure, big data frameworks (e.g., Hadoop, Spark), and relevant certifications is highly valued. Strong problem-solving abilities, effective communication, and the ability to work collaboratively across teams are key soft skills for this role. These attributes are crucial for designing robust data pipelines, ensuring data quality, and enabling organizations to make data-driven decisions efficiently.

What are the most commonly searched types of Data Engineering jobs in Saskatchewan? The most popular types of Data Engineering jobs in Saskatchewan are:
What are popular job titles related to Data Engineering jobs in Saskatchewan? For Data Engineering jobs in Saskatchewan, the most frequently searched job titles are:
What job categories do people searching Data Engineering jobs in Saskatchewan look for? The top searched job categories for Data Engineering jobs in Saskatchewan are:
Data Engineering jobs near you
Infographic showing various Data Engineering job openings in Saskatchewan as of July 2026, with employment types broken down into 100% Full Time. Highlights an 78% In-person, 15% Hybrid, and 7% Remote job distribution, with an average salary of $135,712 per year, or $65.2 per hour.
Data Architect

Data Architect

Brandt

Regina, SK

Full-time

Posted 16 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.

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