Data Analyst

Posted 11 Days Ago
Vancouver, BC, CAN
In-Office
75K-90K Annually
Mid level
Artificial Intelligence • Fintech • Payments • Software • Financial Services
The Role
Own Lending analytics end-to-end: build semantic data models in Snowflake, connect cross-functional data, create dashboards and self-service reporting, and use AI tools to accelerate analysis. Develop and maintain SQL, contribute to data modernization, ensure data quality and standardized KPIs, and partner with Finance, Product, Risk, and Operations to deliver trusted insights and scale analytics.
Summary Generated by Built In
Data Analyst

Location: Remote (Canada)

Department: Data & Analytics

Reports To: Manager, Data Integration & Architecture

Base Salary: $75,000 – $90,000 CAD

About the Role

Orion is looking for a AI-native product/data analyst who owns Lending insight quality and connects customer behavior to business performance. This is an intermediate-level role with a clear growth path toward senior responsibilities — you’ll start by building deep product expertise and delivering trusted analytics, then progressively take on more complex modeling, platform ownership, and strategic work as you grow.

You’ll partner closely with Finance, Product, Risk, and Operations stakeholders to turn business requirements into scalable data models and self-service reporting solutions. You’re someone who actively uses AI tools to work faster and smarter — whether that’s accelerating SQL development, generating documentation, exploring data, or building analytical workflows. AI productivity isn’t a nice-to-have here; it’s part of how we expect this role to operate.

What You’ll DoBusiness Intelligence & Analytics (80%)
  • Own the full Lending analytics domain — from acquisition and application funnel through approval, funding, repayment, retention, and support — building the reporting foundation that helps leaders understand who uses the product, how, and where performance is improving or breaking down.
  • Connect marketing, product, risk, operations, and financial data into a unified view of customer and business performance, ensuring insights reflect the full picture rather than isolated metrics.
  • Design, develop, and maintain semantic data models in Snowflake that translate complex business logic into scalable, reusable structures powering consistent self-service reporting across teams.
  • Build dashboards and analytical views that surface trends, friction points, and opportunities proactively — flagging issues in the funnel, product experience, or operational process before they become larger problems.
  • Partner with Finance, Product, Risk, and Operations to deeply understand KPIs, business processes, and reporting needs; ensure data definitions and metrics remain standardized and trusted across teams.
  • Support Wealth analytics as a secondary area, ensuring reporting approaches stay consistent across Orion's broader financial platform.
  • Actively leverage AI tools (such as Claude, Copilot, Cursor, or similar) to accelerate analysis, automate repetitive work, and raise the quality and speed of your outputs.

Data Solutions & Analytics Engineering (20%)

  • Develop and maintain SQL to support reporting, analytics, and operational decision-making.
  • Contribute to data modernization initiatives, including redesigning existing reporting pipelines.
  • Partner with Data Engineering and Architecture to ensure analytical datasets are reliable, scalable, and well-governed.
  • Apply best practices for testing, monitoring, documentation, and data quality.
  • Support the integration of analytical assets into Mogo’s broader data platform.
Culture & Growth
  •  Bring ownership, curiosity, and a bias toward action — this role rewards people who take initiative.
  • Share knowledge and help strengthen analytical capabilities across the team.
  • Grow into more senior responsibilities over time, including ownership of more complex modeling and AI-powered analytics initiatives.
What You’ll Bring
  • 3–5 years of experience in Business Intelligence, Data Analytics, Analytics Engineering, or a related field.
  • Strong SQL skills with experience designing analytical data models.
  • Product analytics instincts — comfortable with funnel analysis, segmentation, cohort analysis, and customer behavior analysis.
  • Ability to connect user-level behavior to business outcomes like conversion, funding, repayment, retention, revenue, and operational efficiency.
  • Experience with Snowflake, Looker, or similar modern analytics platforms.
  • Solid understanding of dimensional modeling, KPI design, and reporting best practices.
  • Strong judgment on data reliability — you know when a metric is ready to use and when it isn't.
  • Comfortable working with imperfect or evolving data and creating clarity from ambiguity.
  • Strong communication skills — you can explain technical concepts clearly to non-technical stakeholders.
  • Comfortable managing multiple priorities and working directly with business stakeholders.
  • Genuinely curious about AI tools and actively uses them to improve your own productivity and output quality.
Preferred Qualifications
  • Experience with Snowflake Cortex Analyst or similar semantic-layer technologies.
  • Experience with BI and visualization tools such as Looker, Tableau, or Power BI.
  •  Background in financial services, lending, credit risk, or fintech.
  • Exposure to conversational analytics, AI copilots, or natural language query interfaces.
  • Experience supporting data platform modernization or cloud analytics migrations.

 

What Success Looks Like

  • Lending teams confidently rely on your data models and reports to make informed decisions.
  • Semantic models and KPIs are standardized, trusted, and adopted across the organization.
  • Stakeholders view you as the go-to expert for Lending data and metrics.
  • Self-service analytics adoption grows as users gain faster access to accurate, trusted insights.
  • You visibly use AI tools to move faster, document better, and deliver higher-quality work.
  • Over time, you take on more complex platform and strategy work, growing toward senior responsibilities.

Skills Required

  • 3-5 years of experience in Business Intelligence, Data Analytics, Analytics Engineering, or a related field.
  • Strong SQL skills with experience designing analytical data models.
  • Product analytics instincts (funnel analysis, segmentation, cohort analysis, customer behavior analysis).
  • Ability to connect user-level behavior to business outcomes (conversion, funding, repayment, retention, revenue).
  • Experience with Snowflake, Looker, or similar modern analytics platforms.
  • Solid understanding of dimensional modeling, KPI design, and reporting best practices.
  • Strong judgment on data reliability and experience working with imperfect or evolving data.
  • Strong communication skills and ability to work directly with business stakeholders.
  • Comfortable managing multiple priorities and using AI tools to improve productivity.
  • Experience with Snowflake Cortex Analyst or similar semantic-layer technologies.
  • Experience with BI and visualization tools such as Tableau or Power BI.
  • Background in financial services, lending, credit risk, or fintech.
  • Exposure to conversational analytics, AI copilots, or natural language query interfaces.
  • Experience supporting data platform modernization or cloud analytics migrations.
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The Company
HQ: Riga
518 Employees
Year Founded: 2003

What We Do

Mogo Inc. (NASDAQ:MOGO; TSX:MOGO) is a financial technology company building systems for a more intelligent financial future. Through its wholly-owned subsidiaries, including Carta Worldwide and Intelligent Investing, Mogo powers the infrastructure that moves money across businesses and platforms and helps individuals master the art of building wealth through discipline and behavioral edge. Its capital allocation strategy, anchored in Bitcoin and hard assets, reflects a core belief: true value endures when guided by clarity and discipline, not speculation.

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