Director, Analytics & Insights

SQUIRE•Ontario, ON

1d•$200,000 - $230,000•Remote

About The Position

As SQUIRE continues to grow, so does the need for clean, well-defined, and trustworthy data on how the business is performing. As the Director, Analytics & Insights, you will define the standards, taxonomies, and requirements in our core source systems needed for data to flow and report information properly for the business. Based on the data captured, you will consolidate and uncover the drivers behind churn, retention, and conversion, then apply that same rigor to product telemetry and marketing analytics, and bring those insights directly to the leaders who can act on them. Success in this role means the company operates from one consistent and trusted set of metrics built on quality source system data, with leaders able to approach important decisions with a clear understanding of the factors behind them. Your work will directly influence business outcomes with a clear understanding of what matters most, rather than simply report on them. As SQUIRE expands its use of AI, you will bring a thoughtful perspective on where it can add the most value in analytics and ensure our data is prepared to support that work. This role, above all, is central to how SQUIRE makes informed decisions to move faster and scale with confidence.

Requirements

10+ years of experience in an analytics or data function, including 4+ years of people management, with a track record of setting strategy, building analytical data models, and developing teams beyond day-to-day reporting
Demonstrated experience translating data into insights that influence leadership decisions and measurable business outcomes
Experience building analytical models, systems, and practices that create lasting organizational value beyond individual dashboards
Technical fluency across SQL, data modeling, statistics fundamentals, dbt or similar transformation tools, and Looker
Technical judgment and hands-on experience to guide how analytical data is structured and maintain consistent definitions across the business
Thoughtful and clear perspective on AI in analytics, including where it can add meaningful value and where human judgment remains essential
Genuine curiosity about the business, with the ability to move from understanding why something happened to identifying why it matters and what should happen next
Strong leadership and communication skills, with the ability to develop a team and translate complex analytical concepts for executive audiences

Nice To Haves

Experience within a multi-product, marketplace with direct and secondary customers, or SaaS business during a period of scaling or expansion into new verticals, particularly in Salesforce- and Snowflake-based environments.
Experience partnering closely with a Data Engineering function on data platforms and infrastructure without having directly led the infrastructure function.

Responsibilities

Proactively analyze business performance to identify what is changing and why across churn, retention, conversion, unit economics, funnel performance, product adoption, product telemetry, and marketing analytics
Translate complex data into clear insights and recommendations for the leaders and teams positioned to act on them
Define and lead the multi-year strategy for SQUIREâ€™s analytical data, including how it is modeled, structured, and governed to support accurate analysis for scalable business growth and future AI capabilities
Partner closely with Data Engineering (which is responsible for the underlying data platform and infrastructure) to develop scalable and reliable analytical models
Set the strategy for AI-driven analytics, keep our data clean and AI-ready to power both the AI we build into our product and the AI we use to scale the team, from automating first-pass reporting to building on the AI data assistant already in place
Lead Looker as SQUIRE's primary business intelligence platform, including dashboard strategy, reporting improvements, platform cleanup, and self-service reporting
Establish the metric definitions, quality standards, and governance practices needed to maintain trust in the company's data as the business grows in scale and complexity
Lead the company's OKR process and performance readouts, including the cadence, measurement, and reporting used to create visibility and accountability
Lead and grow the analytics function by hiring and developing a team known for quality and reliability across analytics engineering, business intelligence, and analysis