Senior Data Engineer

RP Inc.; Regina; On-site; CAD 100,000 - 110,000; Full time

Job summary

A leading company, RP Inc., is seeking a Data Engineer for a critical role at SaskEnergy in Regina, SK, starting August 2025. This position involves designing and maintaining data pipelines to support advanced analytics. Candidates must possess at least 5 years of recent experience in data management principles and have relevant educational qualifications. This contract role offers a competitive salary and opportunities for contract extensions.

Qualifications

• Minimum 5 years experience in modern data management principles.
• Experience in ETL, data design, and data modeling.
• Relevant job experience in North America.

Responsibilities

• Design, build, and maintain data pipelines and architectures.
• Integrate data from legacy systems and cloud platforms.
• Monitor and troubleshoot database issues.

Skills

SQL Server

ETL

Python

Data Pipelines

Big Data Tools

API Integration

Education

Degree or Diploma in Computer Science, Engineering, Data Sciences

Job description

3 days ago Be among the first 25 applicants

We have received a request for aData Engineer starting August 2025till the end of March 2027,with a possibility of scope extensions. The role will beon-siteat the client’sRegina, SK office.

Please review the details of the role below and let us know:

• If you would be interested in us presenting you for this role.
• Your hourly charges for this role.

Opportunity Overview:

Client:SaskEnergy

Location:Regina, SK (Onsite)

Duration:August 2025 – March 2027 (with potential extensions)

The Deliverables

1.1 Background

SaskEnergy’s Digital, Technology, and Security (DT&S) group is comprised of several functional areas focused on project delivery, architecture, records and information management, security, application and infrastructure management, and enterprise analytics. The DT&S department includes approximately 90 multi-vendor contractors who support the organization’s digital transformation and operational excellence.

The Analytics team at SaskEnergy has evolved significantly since its inception. It now serves as a centralized hub for dashboarding, reporting, analytics, data engineering, and data management services across the organization. The team has made substantial progress in building out enterprise-wide analytics capabilities, but there remains a strong and growing demand for robust data ingestion, transformation, and modeling to support business needs.

As SaskEnergy continues to expand its data-driven culture, the role of Data Engineers is critical in enabling scalable, secure, and high-performance data solutions. Data Engineers work closely with business units and analytics professionals to design, build, and maintain data pipelines and architectures that support advanced analytics, reporting, and operational systems. This includes integrating data from legacy systems, cloud platforms, and modern data lakehouse environments to ensure data is accessible, reliable, and optimized for use.

1.2 Description of Requirements

To be considered, the Data Engineer resource MUST have a minimum of 5 years of recent experience (within the last 7 years) in modern data management principles such as, but not limited to, ETL, data design, architecture, management, modeling, quality, and analytics experience. The successful candidate will demonstrate a broad and solid understanding of these principles.

Successful Data Engineer Candidate Will Have:

Educational & Experience Requirements:

• Degree or Diploma in Computer Science, Engineering, Data Sciences, or a quantitative discipline.
• 5+ years of recent experience in ETL, data design, data architecture, data management, and data modeling.
• Relevant job experience in North America.

Core Technical Skills:

• SQL Server & SSIS:Expert proficiency with SQL Server (on-premises), including stored procedures, and SSIS package-level deployment.
• Data Pipelines:Proven experience designing, creating, and maintaining robust data pipelines and ETL processes.
• Monitoring:Skilled in monitoring and troubleshooting database issues to ensure compliance with policies and regulations.
• Python for ETL:Advanced Python skills applied to developing ETL processes following software development best practices (including automated testing and code reviews).
• Big Data Tools:Proficient in leveraging big data technologies, including PySpark and SparkSQL for large-scale data processing.
• Cloud Expertise:Hands-on experience with cloud-based platforms such as Databricks, Azure Data Factory, and Azure Data Lake.
• Lakehouse Architecture:Knowledgeable in implementing lakehouse architectures using Delta format and optimization strategies.
• API Integration:Experience working with external third-party APIs as ETL sources, including Microsoft Graph APIs to integrate and automate tasks across Microsoft services.
• Automation & Deployment:Familiar with CI/CD processes and tools—including Databricks asset bundles (DABs) for managing workflows—and proficient with version control systems (e.g., Git) for ETL deployments.

Data Management & Communication:

• Understanding of data management principles as outlined by DAMA/DMBoK.
• Ability to provide insights on evolving database integration, storage, and utilization needs.
• Overseeing integration from legacy/on-premises systems to new solutions.
• Clear communication of technical information and the ability to train/support staff.
• Knowledge of data privacy and confidentiality regulations (e.g., PIPEDA).

Typical Activities in This Role Include:

• Work closely with the Enterprise Analytics team to create and maintain ELT processes.
• Assemble large, complex datasets that meet functional/non-functional business requirements.
• Consulting DT&S and Business leaders on data and information management practices and governance.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and other technologies.
• Work with stakeholders including the Executive, to assist with data-related technical issues and support their data infrastructure needs.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our business.
• Work with data and analytics experts to strive for greater functionality in our data systems.
• Championing efforts to improve business performance through enterprise information capabilities, such as master data management (MDM), metadata management, analytics, content management, data integration, and related data management or data infrastructure.
• Provide insight into the changing database integration, storage, and utilization requirements for the company and offer suggestions for solutions.
• Monitor and understand Information Management trends and emerging technologies.

Contract Duration:

The preference for start date is as soon as possible. The contract will be effective for an initial term commencing on the date of award and ending on March 31, 2027. The contract will automatically renew for successive one (1) year terms, up to a maximum of four (4) renewals, unless terminated in accordance with its provisions by either party with at least ten (10) business days' written notice.

Mandatory Requirements (Pass/Fail):

• Candidate must have a Bachelor's degree or technical diploma in Computer Science / Engineering, Data Sciences, or a related discipline, or 5 years of related work experience.
• Candidate must have a minimum of 5 years of experience within the last 7 years working with modern data management principles.
• Candidate must be able to work and be located full-time on-site at SaskEnergy Head Office in Regina, SK, Monday to Friday, 8 am to 5 pm.
• Candidate must be able to attend an in-person interview if shortlisted.

Note:Proponents who do not pass the above mandatory requirements will not be further evaluated. Proposals that do not provide sufficient information for SaskEnergy to confirm the above mandatories are met (at SaskEnergy’s sole discretion) will not be further evaluated.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Contract

• Industries

  Technology, Information and Internet

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