Venn

Data Engineer

Toronto

Sponsorship not specifiedDetected 58 days ago

SQLData EngineeringSEOCRMAccountingLeadershipCommunication

About the role

About Venn Venn is the fastest-growing B2B fintech in Canada.
Business owners are tired of the big banks' monopoly and are looking for modern tools that replace the legacy systems that have been their only option for over 100 years.
We've raised over $26.5M from Tier 1 investors such as Gradient, Left Lane Capital, Intact, and XYZ Venture Capital.

Own Venn's data infrastructure, including pipelines, models, warehouses, and reporting layers that power product, finance, risk, operations, marketing, and leadership decisions.
Build reliable ETL and ELT pipelines that ingest, transform, and structure data from our core product, banking partners, card processors, payment systems, accounting integrations, CRM, marketing tools, and internal systems.
Design clean, trusted data models and analytics layers that make business-critical data easy to access, understand, and use across the company.
Partner with engineering on event schemas, tracking requirements, and measurement architecture to ensure data is reliable, scalable, and built correctly from the start.
Build dashboards, reports, and self-serve workflows for core company metrics, including transaction volume, card spend, FX, balances, revenue, activation, retention, onboarding conversion, acquisition, and risk signals.
Support marketing, growth and sales measurement where needed, including attribution, paid media incrementally, web analytics, CRO, lifecycle analytics, SEO, and organic acquisition reporting.
Experience building and maintaining reliable ETL or ELT pipelines using modern data tooling.
Strong SQL skills and experience building production-grade data models.
Strong communication skills, with the ability to explain technical data concepts and analytical findings in a way that drives business decisions.

5+ years of experience in data engineering, analytics engineering, or a highly technical data role.
Experience working with data warehouses, transformation frameworks, BI tools, and event or product analytics systems.
Strong understanding of data quality, testing, documentation, lineage, metric definition, and analytics reliability.
Ability to translate ambiguous business questions into clean data models, dashboards, and clear recommendations.
Experience partnering with engineering teams on tracking requirements, event schemas, and data infrastructure.
Comfort working cross-functionally with product, engineering, finance, operations, growth, marketing, RevOps, and leadership teams.
Experience with marketing, growth, or web analytics, including attribution, funnel analysis, paid media measurement, SEO analytics, lifecycle analytics, or CRO.
Experience at an early-stage or fast-growing startup.
Experience at a fintech

This listing is sourced directly from Venn's careers page and normalized into a canonical job model.