Manager / Senior Manager, Analytics Engineering

KOHO

1d•CA$170,000 - CA$220,000•Remote

About The Position

KOHO is looking for a Manager or Senior Manager, Analytics Engineering to lead and scale our analytics engineering function. You'll manage a team of 7 Analytics Engineers who build and maintain the data infrastructure that powers critical reporting and business operations across Finance, Payment Operations, Risk, Treasury, Marketing, and Product domains. Beyond team leadership, you'll be responsible for the analytics engineering infrastructure that supports 20+ dbt developers across the organization. This is a high-impact leadership role that combines people management, technical architecture, and strategic partnership with business stakeholders to ensure KOHO's data foundation scales with our ambitious growth.

Requirements

5+ years in analytics engineering, data engineering, or similar technical data roles, including 2+ years managing technical teams
Proven people leader: Track record of hiring, developing, and retaining high-performing individual contributors
Experience scaling teams: You've built or grown technical teams and established practices that enable sustainable growth
Outcome-Obsessed Leader: You translate complex data challenges into clear business choices, moving comfortably between technical mentorship and high-level roadmapping to ensure your team is always solving KOHO’s highest-leverage problems.
Expert-level dbt knowledge: Deep experience with dbt Core/Cloud, complex projects, advanced materializations, macros, packages, and project architecture
Strong SQL and data modelling skills: Proficiency with dimensional modelling, event modelling, and performance optimization
Modern data stack fluency: Experience with dbt, Git, CI/CD, data warehouses (Redshift is a plus), and orchestration tools
Infrastructure mindset: Understanding of data platform architecture, scalability, and reliability patterns
Strategic thinker: Able to translate business objectives into technical roadmaps and prioritize effectively
Exceptional communicator: Adapt messaging for different audiences from C-suite to individual contributors
Stakeholder management: Navigate competing priorities, manage expectations, and build trusted partnerships across the organization
Results-oriented: Focus on outcomes and business impact, not just technical outputs
Commercial Acumen: You understand the unit economics of a fintech and how data quality directly impacts our bottom line and regulatory standing.
High ownership: You take responsibility for outcomes and empower your team to do the same
Collaborative: You build bridges across teams and create environments where diverse perspectives thrive
Adaptable: You thrive in fast-moving environments and can shift priorities without losing momentum
AI-forward: You're excited about leveraging AI to amplify team productivity and effectiveness

Nice To Haves

Experience in fintech, banking, or highly-regulated industries
Background in credit, payments, or financial operations data
Experience managing remote-first or distributed teams

Responsibilities

Build and develop a high-performing team: Mentor, and grow the Analytics Engineers through coaching, performance management, and career development
Foster a culture of excellence: Set standards for code quality, documentation, and collaboration while building psychological safety and autonomy
Enable team success: Build systems, prioritize work strategically, and ensure your team has the context and resources to deliver impact
Drive performance: Conduct regular 1:1s, performance reviews, and calibrations aligned with KOHO's high-performance culture
Develop a long-term talent strategy, identifying skill gaps and creating career pathways that ensure KOHO attracts and retains top-tier analytics engineering talent.
Own the analytics engineering platform: Maintain and evolve the data infrastructure supporting 20+ developers across analytics engineering and broader data teams (product analysts, business analysts, and developers)
Architect for scale: Define technical strategy, standards, and best practices for data modelling, pipeline development, and data quality
Optimize performance: Monitor infrastructure health, drive query optimization, and ensure reliability across critical data pipelines
Champion technical excellence: Establish governance frameworks, code review standards, and documentation practices
Partner with domain leaders: Collaborate with Analytics, Finance, Payment Operations, Risk, Treasury, and Product teams to understand their data needs and translate them into technical roadmaps
Drive cross-functional initiatives: Lead multi-team projects that require coordination across analytics engineers, data engineers, analysts, and business stakeholders
Ensure timely delivery: Balance competing priorities, manage stakeholder expectations, and deliver high-quality data products that drive business outcomes
Bridge technical and business: Translate complex technical concepts for non-technical audiences and business requirements into technical solutions
Act as a Strategic Consultant to the C-suite: translating complex technical debt or architectural needs into clear business risks and opportunities.
Evolve the practice: Identify opportunities to improve processes, tooling, and team effectiveness
Leverage AI: Explore and implement AI-assisted development practices to increase team productivity
Build organizational capability: Create learning opportunities and knowledge-sharing practices that upskill the broader organization