Integrated Planning Faculty Analyst

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Job Requisition ID:

2026-03449

Time Type:

Full time

Employee Group:

Staff

Job Category:

Analytics and Reporting

Employment Type:

Permanent

Department:

Faculty of Science - Dean of Science Office - Strategic Initiatives

Hiring Range:

$87,620.25 - $109,525.32

Posting Information:
This posting is for an existing vacancy.

The internal posting deadline for this position is November 5 2026, at 11:59PM.

Job Description:

Primary Purpose

The Integrated Planning Faculty Analyst (IPFA) is responsible for the design, development, and delivery of integrated data systems, analytical models, and reporting solutions that support strategic, operational, and financial planning within the Faculty of Science.

The role combines advanced data analysis with systems development and automation to enable scalable, reliable, and accessible data products for a wide range of stakeholders. The IPFA leads the development of data pipelines, analytical tools, and dynamic reporting environments, ensuring that high-quality data is transformed into actionable insight for evidence-based decision-making.

The IPFA provides expert advice and technical leadership in data architecture, analytics, and reporting, contributing to Faculty of Science planning, process improvement, and performance monitoring.

Key Accountabilities

Integrated Data Systems Design and Development

• Designs, develops, and maintains scalable data systems, pipelines, and architectures to support Faculty-wide planning, reporting, and analytics needs

• Develops and implements data models, schemas, and business rules to improve data consistency, accessibility, and usability

• Integrates data from multiple institutional and external sources into cohesive, standardized datasets for analysis and reporting

• Applies modern development methodologies to build and maintain backend systems and data workflows

• Ensures systems are robust, secure, and aligned with institutional data governance and privacy requirements

Advanced Analytics and Strategic Planning Support

• Develops analytical models, forecasts, and scenario analyses to support strategic planning, enrolment management, and resource allocation

• Analyzes trends, patterns, and performance indicators to inform Faculty priorities and decision-making

• Synthesizes complex data into insights that support faculty initiatives, financial planning, and faculty strategy

• Applies quantitative and qualitative methods to address complex research and planning questions

Automation and Data Engineering

• Designs and implements automated data processing, transformation, and validation workflows to improve efficiency and reduce manual effort

• Develops reusable scripts and tools (Python, R, SQL, etc.) to support data preparation, integration, and analysis

• Leads the automation of recurring reporting processes and data updates

• Establishes best practices for reproducibility, version control, and documentation of data processes

Reporting, Visualization and Data Products

• Designs and delivers dynamic dashboards, reports, and interactive tools (Power BI, web-based applications, etc.) to support diverse stakeholder needs

• Develops user-facing data products that enable self-service analytics and exploration of planning parameters

• Ensures data is communicated clearly through compelling visualizations, narratives, and presentations

• Tailors reporting outputs for different audiences, including senior leadership, academic units, and external stakeholders

Data Governance, Quality and Stewardship

• Ensures the accuracy, integrity, and consistency of Faculty data through validation, cleansing, and standardization processes

• Identifies and resolves data quality issues, implementing sustainable solutions to improve reliability

• Defines and maintains standards for data structures, metadata, and documentation

• Supports compliance with privacy, confidentiality, and ethical data practices

Stakeholder Engagement and Technical Consulting

• Consults with stakeholders to identify business needs, define requirements, and translate them into technical and analytical solutions

• Acts as a bridge between technical and non-technical audiences, translating complex concepts into actionable insights

• Provides expert advice to Faculty leadership and administrative units on data strategy, tools, and systems

• Builds collaborative relationships across campus to align data initiatives and promote information sharing

Innovation, Continuous Improvement and Technical Leadership

• Identifies opportunities to improve data systems, processes, and analytical capabilities across the Faculty

• Evaluates and implements new tools, technologies, and methodologies to enhance data and reporting capabilities

• Applies abstract and systems-level thinking to design scalable, reusable solutions that benefit multiple stakeholders

• Maintains current knowledge of emerging trends in data analytics, data engineering, and higher education planning

Required Qualifications

Education

• Bachelor’s degree in Data Science, Computer Science, Statistics, Economics, or a related discipline

• Combination of education and relevant experience in analytics and systems development may be considered
• Completion of Decisions training is an asset

Experience

• Minimum 5+ years of progressively responsible experience in either advanced data analysis and decision support using large and complex datasets, with demonstrated capability in systems development or automation, or data systems, database, and interface/application development supporting complex datasets, with demonstrated capability in data analysis and interpretation

• Demonstrated experience in developing data pipelines, systems, or applications supporting analytics workflows

• Experience across the data lifecycle, including data acquisition, transformation, modelling, and reporting

• Experience with project planning and delivering technical solutions in a collaborative environment

Knowledge/Skills/Abilities

• Advanced expertise in data analysis, statistical methods, and data interpretation

• Strong programming skills (e.g., Python, R, SQL) and experience with data processing frameworks

• Knowledge of database design, data modelling, and systems development methodologies

• Experience with data visualization tools (e.g., Power BI) and development of interactive dashboards

• Ability to design and implement scalable, automated data solutions

• Strong problem-solving skills, including the ability to apply abstract thinking to complex challenges

• Excellent communication skills to convey complex technical information to diverse audiences

• Ability to balance multiple priorities and work independently in a dynamic environment

Equity Statement

The University of Waterloo acknowledges that much of our work takes place on the traditional territory of the Neutral, Anishinaabeg, and Haudenosaunee peoples. Our main campus is situated on the Haldimand Tract, the land granted to the Six Nations that includes six miles on each side of the Grand River. Our active work toward reconciliation takes place across our campuses through research, learning, teaching, and community building, and is coordinated within the Office of Indigenous Relations.

The University values the diverse and intersectional identities of its students, faculty, and staff. The University regards equity and diversity as an integral part of academic excellence and is committed to accessibility for all employees. The University of Waterloo seeks applicants who embrace our values of equity, anti-racism and inclusion. As such, we encourage applications from candidates who have been historically disadvantaged and marginalized, including applicants who identify as First Nations, Métis and/or Inuk (Inuit), Black, racialized, a person with a disability, women and/or 2SLGBTQ+.

Positions are open to qualified candidates who are legally entitled to work in Canada.

The University of Waterloo is committed to accessibility for persons with disabilities. If you have any application, interview, or workplace accommodation requests, please contact Human Resources at [email protected] or 519-888-4567, ext. 45935.