Weâre on a mission to make financial services better for every Canadian. That means no hidden fees, no predatory interest rates - just financial products designed to help our users spend smart, save more, and build real wealth. Weâre a performance organization with a strong heart: we care deeply about outcomes, and everything ties back to our mission - to financially empower a generation of Canadians.
At KOHO, weâre not your average 9-5. We believe real impact comes from people who are trusted, empowered, and supported to do their best work - without sacrificing their lives to do it. We prioritize work-life integration, not just work-life balance. That means asynchronous collaboration, flexible hours, and a remote-first setup built around autonomy and high trust.
KOHO is entering its next chapter - leaner, smarter, more AI-integrated. Weâre building for impact, not bureaucracy. If you thrive in environments that value clarity, ownership, and bold thinking, youâll fit right in.
KOHO is looking for an Analytics Engineer, Credit Risk, to build and scale robust reporting pipelines that power complex credit reporting. In close collaboration with the Credit Team, you'll partner with Payment Operations, Tech, Security, Risk, and Finance teams, as well as fellow Analytics Engineers, on multi-month builds, ensuring our data infrastructure keeps pace with ambitious credit product initiatives.
This is a new role bridging analytics engineering excellence with credit data transformation needs. You'll own the technical backbone that enables funds to be accurately processed and reported internally and to financial authorities.
Lead complex financial pipeline builds: Design and develop scalable data pipelines supporting banking processes, from scoping through delivery
Collaborate cross-functionally: Partner with Credit, Payment Operations, Tech, Security, Risk, and Finance teams to define data requirements
Build credit reporting infrastructure: Create reliable, performant operational data models that power internal and external reporting, audits, and money movements.
Design scalable data models: Apply modelling frameworks (one big table, entity tables, event streams, Kimball) tailored to credit reporting use cases
Optimize and monitor: Maintain pipeline health, optimize query performance, and implement data quality monitoring
Enable the team: Document solutions, establish best practices, and help upskill fellow Analytics Engineers and Analysts
Integrate cross-functional data: Work across domain boundaries to unify financial data into cohesive reporting structures
3+ years of experience in analytics engineering, data engineering, or similar data roles
Advanced DBT expertise: Comfortable with complex DBT projects, various materializations, such as incremental, table, view, etc. Familiar with snapshots, variables, macros, and Jinja.
Strong SQL skills with a focus on query optimization and performance
Experience with modern data stack: DBT Core and/orDBT Cloud, Git. A plus if experience with Redshift.
Collaborative mindset: You thrive working alongside analysts, PMs, and engineers to translate business requirements into technical solutions
Strong communicator: You adapt communication to different audiences and connect technical work to reporting outcomes
Proactive problem-solver: You identify opportunities for improvement and take initiative without waiting to be asked
AI-curious: Experience or strong interest in leveraging AI tools for development workflows. Strong foundations of AI-assisted development are a plus.
Experience in fintech, credit, and/or banking environments
Experience with highly-regulated domains
The budgeted salary range for this role is $100,000 - $135,000 CAD / year.
At KOHO, we are dedicated to providing pay transparency to all candidates. Compensation at KOHO is determined through various factors including but not limited to: comparable salary market data within Canada, technical skill assessment, a holistic view of previous work history, and internal pay equity with other KOHO team members.
KOHO est Ă la recherche dâun·e Analytics Engineer, CrĂ©dit pour concevoir et faire Ă©voluer des pipelines de reporting robustes qui alimentent des rapports de crĂ©dit complexes. En Ă©troite collaboration avec lâĂ©quipe CrĂ©dit, vous travaillerez avec les Ă©quipes OpĂ©rations Paiements, Tech, SĂ©curitĂ©, Risque et Finance, ainsi quâavec dâautres Analytics Engineers, sur des projets de plusieurs mois afin de garantir que notre infrastructure de donnĂ©es soutient nos initiatives ambitieuses en matiĂšre de produits de crĂ©dit.
Il sâagit dâun nouveau rĂŽle qui fait le pont entre lâexcellence en analytics engineering et les besoins de transformation des donnĂ©es de crĂ©dit. Vous serez responsable de la colonne vertĂ©brale technique qui permet de traiter et de dĂ©clarer les fonds avec prĂ©cision, tant Ă lâinterne quâauprĂšs des autoritĂ©s financiĂšres.
Diriger des projets complexes de pipelines financiers :
Concevoir et dĂ©velopper des pipelines de donnĂ©es Ă©volutifs qui soutiennent les processus bancaires, de la dĂ©finition du pĂ©rimĂštre jusquâĂ la livraison.
Collaborer de façon transversale :
Travailler en partenariat avec les équipes Crédit, Opérations Paiements, Tech, Sécurité, Risque et Finance afin de définir les exigences en matiÚre de données.
Construire lâinfrastructure de reporting de crĂ©dit :
Créer des modÚles de données opérationnels fiables et performants qui soutiennent les rapports internes et externes, les audits et les mouvements de fonds.
Concevoir des modÚles de données évolutifs :
Appliquer des cadres de modĂ©lisation (one big table, tables dâentitĂ©s, flux dâĂ©vĂ©nements, Kimball) adaptĂ©s aux cas dâusage du reporting de crĂ©dit.
Optimiser et surveiller :
Maintenir la santĂ© des pipelines, optimiser les performances des requĂȘtes et mettre en place des mĂ©canismes de surveillance de la qualitĂ© des donnĂ©es.
Soutenir lâĂ©quipe :
Documenter les solutions, établir les meilleures pratiques et contribuer au développement des compétences des Analytics Engineers et Analystes.
Intégrer les données transversales :
Travailler au-delà des domaines pour unifier les données financiÚres dans des structures de reporting cohérentes.
Plus de 3 ans dâexpĂ©rience en analytics engineering, data engineering ou dans des rĂŽles similaires liĂ©s aux donnĂ©es
Expertise avancĂ©e en DBT : Ă lâaise avec des projets DBT complexes et diffĂ©rentes matĂ©rialisations (incremental, table, view, etc.). Connaissance des snapshots, variables, macros et Jinja.
Excellentes compĂ©tences en SQL, avec un accent sur lâoptimisation et la performance des requĂȘtes
Expérience avec une stack de données moderne : DBT Core et/ou DBT Cloud, Git. Une expérience avec Redshift est un atout.
Esprit collaboratif : vous aimez travailler avec des analystes, PM et ingĂ©nieurs pour traduire les besoins dâaffaires en solutions techniques
Excellentes aptitudes en communication : vous adaptez votre message à différents publics et reliez le travail technique aux résultats de reporting
Proactif·ve et orienté·e solutions : vous identifiez les opportunitĂ©s dâamĂ©lioration et prenez des initiatives sans attendre quâon vous le demande
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