Job Description:
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 warehouse. In 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 sources—with 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 December 31, 2028.
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 degree—preferably 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: Open until a suitable candidate is found
A cover letter and resume should be submitted in one .pdf document. Please title your .pdf document as follows: [Last Name], [Requisition Number], [Document Title].pdf (ex. Smith, 4321, CV.pdf).
