Data Engineer

Responsibilities

• 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.

Qualifications

• 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.
• 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