Top Tech Jobs & Startup Jobs in Toronto

Lead the Insurance Setup engineering team, drive delivery of configuration and insurance features, balance new product discovery with technical health, coach and grow engineers, partner closely with Product and Design, influence cross-team initiatives, and responsibly explore AI adoption.

Build and maintain the product analytics data foundation: design scalable dbt models, define semantic models and governed metrics, partner with Engineering on instrumentation, certify datasets for BI tools, monitor pipelines and data quality, and use AI to accelerate analytics engineering workflows.

Build and operate the core BI platform: own ingestion, integration, modular dbt pipelines, and enterprise data models. Establish data quality, testing, governance, observability, and CI/CD. Monitor platform health, certify pipelines and data products, and mentor analytics engineers to enable trusted, self-service analytics and AI-augmented workflows.

Own and maintain core financial datasets and dbt models; write complex SQL; build and optimize Looker dashboards; troubleshoot data quality; and deliver reconciled, actionable financial insights to Finance and Payments stakeholders.

Lead strategic growth analyses and modeling across marketing, pricing, and go-to-market initiatives. Own end-to-end analyses from problem structuring to executive presentation, forecast and monitor performance, design data sourcing, partner across Marketing and GM teams, and build repeatable frameworks and self-serve tools to drive growth decisions and implementation.

Lead development of customer-facing payments features, turning core payments infrastructure into reliable, scalable capabilities (surcharging, pricing, automation). Drive architecture and implementation decisions, collaborate closely with product, communicate frequently in a distributed team, and adopt AI tools to improve the software development lifecycle and team practices.

Lead the Growth pod as the first dedicated data hire: build data infrastructure connecting event, product, GTM, and financial data; define metrics and run experiments with proper power analysis; build predictive models and reporting/automation; proactively surface insights and embed with Product, Engineering, and Design to drive activation, expansion, and retention. Bring applied AI to improve growth outcomes.

Lead design and implementation of Jane's customer data infrastructure: own event collection, pipelines, CDP tooling, schema governance, identity resolution, and attribution. Work cross-functionally with marketing, BI, product, and engineering to set standards, evaluate tooling (e.g., RudderStack), ensure privacy-compliant instrumentation, and build reliable, consistent data delivery to the warehouse.

Provide high-quality, real-time customer support, lead demos and onboarding, troubleshoot billing and insurance issues, and tailor communication across phone, chat, and video while learning deeply about the product and improving processes.

The Director of Product Management will lead product strategy across infrastructure, software enablement, and customer-facing platforms, enhancing both technical and user experience while managing a team of product managers.