ANALYTICS ENGINEER

Vetster (vetster.com) is the world’s fastest-growing veterinary telehealth and pet care marketplace. Since our launch in 2020, we have established ourselves as a leader in the rapidly growing pet care industry. Named Pet App of the Year, Vetster makes it easier for pet owners to connect with the veterinary care they need - anytime, anywhere,
We know that by empowering pet owners with easy-to-use, convenient services and an open marketplace, we can move the industry forward, create professional opportunities in the veterinary community, and fundamentally improve animal well-being and access to care. The work we are doing is groundbreaking and is changing lives.
We work in cross-functional teams and believe ownership and accountability, along with trust, respect and inclusion are core tenets of success in our new working paradigm. At all levels, successful Vetster team members are those who seek to grow their careers and who share our ambition to build a global high-growth brand. Please note this role is hybrid, with 2 days per week in our office in midtown Toronto at Yonge and Summerhill.

• Model & Orchestrate Data — Build green-field dbt models (Postgres ➞ Redshift), establish automated tests, and manage CI workflows (GitHub Actions, Hevo).
• Engineer for Scale — Refactor and modularize legacy pipelines (SQL/Python), reduce costs, improve speed, and set best-in-class data-orchestration standards.
• Advance Predictive Analytics — Productionize modals (e.g. churn, LTV, propensity) ensuring scalability and reliability using industry standard tools (Python, scikit-learn, pandas).
• Enable Self-Serve Insights and Analytics — Craft curated Metabase dashboards (or Looker/PBI/Tableau) and empower teams with training to tell compelling stories.
• Champion Data Quality — Own pipeline monitoring, anomaly detection, and release checklists to ensure every downstream asset is trusted.
• Experimentation: Lead the design, execution, and analysis of experiments, including multivariate hypothesis testing. Work closely with cross-functional teams to identify and capitalize on opportunities for innovation.
• Cross-functional Collaboration: Serve as a key connector between departments, ensuring that data-driven strategies align with broader company goals. Promote a collaborative approach to problem-solving and solution development.
• Event Data Management: Lead the scoping, implementation, and management of front-end web and app event data. Collaborate with engineering teams to ensure accurate and efficient deployment.
• Everyone gets their hands dirty here. Whether it’s wrangling data or jumping into a fire drill, we show up and ship.