Data Engineer

The Office of Institutional Research and Planning (OIRP) has primary responsibility for institutional strategic planning surveying and institutional data analysis at Mount Royal. The Office collects analyzes interprets and reports data and information to support decision making planning and evaluation across the institution. Academic quality assurance is a function of prime importance in a university and OIRP supports academic units in conducting cyclical program reviews and developing new programs through data analysis and coordination. OIRP is responsible for providing quality information and institutional research to inform strategic planning assessment development and accountability and for providing leadership in the management of data as a University resource.

This position reporting to the Director Institutional Research and Planning will lead the design development and optimization of our Microsoft Fabric data lakes and enterprise data this role you will be the driving force behind our transition to modern data warehousing solutions leveraging Microsoft Fabric and the broader Azure ecosystem. The role will be tasked with architecting complex data pipelines orchestrating ETL/ELT workflows and integrating disparate data sourceswith a specific focus on extracting and transforming data from our Ellucian Banner ERP system. The ideal candidate brings a deep technical mastery of SQL DevOps Git Spark Python dataflows deployment and data pipelines a passion for performance optimization and the ability to turn raw data into a strategic asset.

Collaboration with colleagues in the Office of Institutional Research and Planning (OIRP) Department ITS and engaging experts across other departments are critical components of this role to ensure optimized data integration high data quality and fault-tolerant pipelines.

This is a full-time limited term position working 35 hours per week until March 31 2027.There is a possibility of extension for another year with the right candidate.

Data Engineering
Design develop and implement Microsoft Fabric data lakes enterprise data warehouse and BI solutions leveraging various enterprise data warehouse methodologies models and technology stack.
Architect and manage the cloud data infrastructure on Microsoft Fabric ensuring high availability security and performance.
Execute hands-on ELT/ETL and BI development delivery tasks specifically; ETL job development technical data model design and development of deployment pipelines from dev/UAT environment to production environment.
Implement robust monitoring alerting and data validation checks to ensure data quality accuracy and reliability of the data pipelines.
Identify design and implement internal process improvements: automating manual processes optimizing data delivery and redesigning infrastructure for greater scalability.
Develop data designs scripts and code for new projects of moderate to high complexity.
Design dimensional and relational structures optimized for reporting and analytics.

Data Modelling
Understand and gather data and business requirements from various departments and division at MRU and transform them into data warehouse solutions and semantic data models.
Contribute to driving reporting automation and perform quality assurance to support the development of scalable and sustainable data products.
Build and architect semantic data models datasets and self-service analytical solutions.
Develop strategies for data modeling design and implementation to meet requirements for metadata management operational data stores and ELT/ETL environments.

Collaboration and Engagement
Engage subject matter experts across OIRP ITS and various other departments to provide support and solve complex technical problems and deliver data solutions.
Identify cross-institutional issues or problems related to data quality and system integration and recommend solutions and alternatives toward the effective implementation of data quality standards and governance.
Collaborate with data specialist business analysts management and other team members to gather requirements and deliver user-centered solutions.
Ensure compliance with institutional and ITS technology standards policies and security requirements.
Document planned and unplanned changes and support problem resolution as required.

• A Bachelor degreepreferably in computer science computer/software engineering or other relevant programs within data engineering data analysis artificial intelligence or machine learning.
• Direct experience in data warehousing ETL/ELT processes database design with strong verbal and written communication.
• Must have 5-8 years of experience as a data engineer integrating ERP systems (e.g. Banner PeopleSoft Workday) designing data pipelines and building enterprise data warehouses.
  • A combination of education and work experience is required to perform the necessary data requirements gathering and analysis integration of on-prem data into the cloud lakehouse design of the cloud enterprise data warehouse and semantic models and ongoing optimization of data integration processes.
• Must have experience using Microsoft Fabric technology stack including Pipelines PySpark SparkSQL SparkR Dataflows DAX Notebooks and Semantic Models - having experience building enterprise data warehouses must be identified in your resume.
• Fluent in creating data processing frameworks using T-SQL Python PySpark SparkSQL and Microsoft Fabric technology stack.
• Experience in delivering data solutions with expert knowledge of CI/CD DevOps Git data structures data quality management dimensional modelling and star-schema design.
• Experience with Power Platform (Power Apps Power Automate) is an asset.
• Excellent time-management and organizational skills with the ability to handle conflicting demands and prioritize effectively.
• Proven abilities to take initiative and be innovative.
• Analytical mind with a problem-solving aptitude.

Closing Date: June 7 2026

A cover letter and resume should be submitted in one .pdf document. Please title your .pdf document as follows: Last Name Requisition Number Document (ex. Smith 4321 ).