Job description
Business Intelligence Analyst
For accessibility assistance with this document please telephone Elections Ontario at 1-888-668-8683 or Fax at 1-866-714-2809. You can TTY at 1-888-292-2312 or via email at info@elections.on.ca.
Position Status: Permanent
Posting Status: Open
Location: (On-site) 26 Prince Andrew Place, North York, ON, M3C 2H4
Salary Band: $75,185 - $105,116 per year
Hours of Work: 36.25 per week
Posting Date: October 13, 2026
Closing Date: October 27, 2026
Who we are
The Office of the Chief Electoral Officer (Elections Ontario) is an independent, non-
partisan office of the Legislative Assembly of Ontario, responsible for administering
provincial elections, by-elections, and referenda.
At the heart of our work is a commitment to democracy – making voting easy and
accessible for all electors, while maintaining the integrity, security, and transparency of
the electoral process.
Join our team
The Elector Data & Analytics Division is seeking a skilled and curious Business
Intelligence Analyst to help assess the accuracy and the quality of Ontario's Register of
Electors and related geographic products and services. In this role, you will apply data
management, spatial analysis, research, and information modelling techniques to support
the Permanent Register of Electors of Ontario. You will work with large and complex
datasets, including elector, address, property, and geographic information, to deliver
insights that support decision making.
What you can expect in this role
Reporting to the Manager, Business Intelligence, you will:
• Support the development and delivery of advanced analytics and research pertaining
to the quality of information in the Permanent Register of Electors of Ontario.
• Identify, integrate, and maintain information and models for assessing the provincial
register of electors’ data. This involves integrating datasets of addresses, properties,
and a repository of geographical and administrative spatial assets.
• Define, implement, and track key quality metrics and performance indicators for
evaluating the quality of information maintained in the provincial register and
disseminated as list and geographical products and services to provincial and
municipal stakeholders.
• Provide education and guidance to team members and external stakeholders on
understanding business intelligence research initiatives.
• Consult and collaborate with staff from other functions to create actionable
recommendations. Advise the Manager on the implications of business proposals,
projects, and decisions affecting register information.
What you need to qualify
Required skills and experience:
• Demonstrated knowledge of information modelling, data analysis, data processing
methodologies, and research methods.
• Experience writing SQL queries, procedures, and data processing workflows,
preferably using Microsoft SQL Server/T-SQL.
• Experience using version control systems, preferably Git, with a preference working
with Azure DevOps.
• Demonstrated experience in analyzing tabular and spatial data using GIS software,
tools, and datasets.
• Experience with business intelligence applications and development tools such as
Microsoft Power BI, to design appropriate Business Intelligence applications,
measures, and tests to evaluate data.
Assets:
• Experience in a legislative, regulatory, public sector, or broader public service
environment, particularly where data management and measurement frameworks
support statutory obligations.
• Experience conducting quantitative research and applying statistical methodologies
to support decision making.
• Experience working with Statistics Canada population and demographic datasets.
• Experience working with Ontario-based datasets such as those from Land Information
Ontario (LIO) and TERANET.
• Experience with statistical tools or programming languages such as R, SAS, Python or
similar analytical platforms.
• Experience in automating processes such as the generation of quantitative reports
would be an asset.
• Education: A degree in one of the following disciplines: Mathematics, Statistics,
Geographic Information Systems (GIS), Political Science, Computer Science, or a
related field.
• Must be legally entitled to work in Canada.
This role requires in-office presence five (5) days per week. There is no hybrid option.
The successful candidate will be required to complete criminal background and social
media checks as part of the hiring process.
How to apply
Our recruitment process reflects our mission to uphold the integrity and accessibility of
the electoral process and to manage elections in an efficient, fair, and impartial manner.
We offer career growth opportunities and a competitive rewards program.
Please submit your cover letter and resume as one PDF attachment, using format: EO-
2026-116, First Name Last Name in the subject line, to jobs@elections.on.ca, no later
than 4:00 PM on October 27, 2026.
Please note: Applications without a cover letter will not be accepted.
We thank all applicants for their submission, but only those candidates selected for an
interview will be contacted.
How to request an accommodation
Elections Ontario is an equal-opportunity employer. We are committed to fostering an
inclusive, equitable, and accessible environment, where all employees feel valued,
respected, and supported.
Under the Accessibility for Ontarians with Disabilities Act and the Ontario Human Rights
Code, we provide accommodation for applicants with disabilities throughout the
recruitment and selection process. If you require a disability-related accommodation to
participate, please call 1-888-668-8683, send a fax to 1-866-714-2809, TTY at 1-888-292-
2312 or email hr@elections.on.ca.
At Elections Ontario, all resumes are screened by the Talent Acquisition team and Hiring
Managers, without the use of AI. Criminal record checks also do not use AI. However, AI
technology is used when conducting social media checks.
Elections Ontario posts salaries in accordance with ESA pay/transparency legislation.
Individual salaries within the anticipated salary range are determined through various
factors, including but not limited to internal equity, education, relevant experience,
knowledge and applicable skill sets.