Senior Data Analyst Ontario

Next Horizon is here. Fueled by investments in talent and technology, our bold strategy to transform is nearly complete.

At Gore Mutual, we’ve always set ourselves apart as a modern mutual that does good. Now, we’re proudly building on that legacy to transform our company—and our industry—for the better.

Our path forward sharpens our focus on business performance, driven by leading technology, innovation and an agile, high-performing culture. With Gore Mutual and Beneva announcing their intent to merge in 2026, we’ll be uniting two well-established, financially strong, and trusted brands to become the strongest mutual insurer in Canada, ensuring Canadians have purpose-driven insurance options for generations to come. Come join us.

The Senior Data Analyst will identify business metrics and reporting solutions to enhance the business intelligence function. This is a hands‑on role responsible for developing and maintaining user‑centric reporting and providing subject matter expertise to business leaders in alignment with business strategy and organizational needs. This role involves curating, monitoring, tracking, and notifying on data and insights across the enterprise.

• Produce analysis that will support decision making at a higher level. This analysis often results from unfolding business opportunities and issues and helps to infer the overall direction of business performance.
• Design and prototype new analyses, reports, visualizations, and data analytics in accordance with data governance and reporting design standards
• Identify business metrics and reporting solutions that will improve the overall effectiveness and efficiency of the Business Intelligence function
• Make sense of large amounts of disparate data to tell a consistent story focused on key strategic decision‑making for executives and management

• Data storytelling:
  Crafting a narrative around data to make insights more engaging and understandable.
• Data monitoring:
  Continuously tracking data to ensure accuracy and identify trends or anomalies.
• Data reconciliation:
  Ensuring consistency and accuracy by comparing and aligning data from different sources.
• Creation of reporting solution in Power BI:
  Developing interactive and visually appealing reports using Power BI to facilitate data‑driven decision‑making.
• Creation of data asset using SQL or Python that is used in consumption of downstream analysis (OBT creation)

• Data storytelling:
  Crafting a narrative around data to make insights more engaging and understandable.
• Business contextualization of technical output:
  Translating technical data into business‑relevant insights to strategic decisions.
• Data reconciliation:
  Ensuring consistency and accuracy by comparing and aligning data from different sources.
• Benefits Realization Quantification:
  Measuring the tangible and intangible benefits achieved from a project or initiative.
• Tracking of Targets and overall corporate performance:
  Monitoring key performance indicators (KPIs) to assess progress towards goals and overall business health.

• Data modelling:
  Designing the structure of data solution to organize and manage data efficiently.
• Requirements gathering:
  Collecting and documenting the needs and expectations of stakeholders for a project.
• Data reconciliation:
  Ensuring consistency and accuracy by comparing and aligning data from different sources.
• Creation of reporting solution in Power BI:
  Developing interactive and visually appealing reports using Power BI to facilitate data‑driven decision‑making.
• Creation of data asset that is used in consumption of downstream analysis (OBT creation):
  Building a data resource that supports further…