Senior Product Manager (PDI) - Canada

7+ years of product management experience, preferably in fintech, consumer finance, lead generation, or data-centric products. Demonstrated success launching impactful data or platform initiatives at scale. Strong data literacy—able to write SQL, understand relational models, and reason about data flows end-to-end. Deep understanding of ETL/ELT processes, APIs, data pipelines, and integration patterns. Ability to hold technical conversations with senior engineers and guide technical tradeoffs. Strong understanding of performance marketing and lead generation economics. Exceptional communication and stakeholder influence skills across technical and non-technical teams. Proven ability to translate ambiguous business needs into clear product requirements. Understanding of Lakehouse architectures, query engines, and compute platforms (e.g., Spark, Trino, Databricks, Snowflake). Experience building or shipping APIs, SDKs, data contracts, or client integration frameworks. Familiarity with data observability, telemetry, instrumentation, and monitoring best practices. Hands-on experience managing high-volume, multi-source datasets from a product perspective.

Own the Partner Data Roadmap: Develop, maintain, and communicate a clear product roadmap for partner data ingestion, transformation, and reporting. Identify and prioritize the highest-impact opportunities using business metrics, customer feedback, and technical insights. Communicate tradeoffs clearly and gracefully to stakeholders when initiatives cannot be prioritized. Drive Data Quality and Reliability: Ensure accuracy, completeness, and reliability across all partner data pipelines. Work with teams to reduce data quality issues and build a robust data observability layer. Uncover Hidden Opportunities: Identify problems and opportunities in underlying data workflows. Partner and Influence Across the Organization: Collaborate with cross-functional partners to ensure partner data powers business functions. Translate business needs into clear technical requirements that guide engineering execution. Mentor team members and cultivate a culture that understands the value and impact of data products.