Who are we looking for: Senior Analytics Engineer on the ACV Capital team is an expert practitioner who transforms raw data into trusted, decision-ready models and reports that drive the lending business forward. Sitting at the intersection of data engineering and business intelligence, this role owns the full analytics stack - from dbt model design and data quality to Omni BI dashboards - and partners directly with Capital leadership to surface insights on lead targeting, loan origination, account management, dealer servicing, and operational compliance. A key objective of this role is reducing ad-hoc analytical bottlenecks over time.

You will be expected to answer urgent business questions quickly and directly, while systematically building the underlying dbt models, metric definitions, and BI layer in a way that enables self‑serve analytics - including AI‑assisted querying - so that Capital stakeholders can answer common questions themselves.

What you will do (Responsibilities) Analytics Modeling &

• Data Quality - Design, build, and maintain dbt models (staging, intermediate, production layers) that serve as the single source of truth for Capital KPIs, with machine-readability in mind - Enforce data quality through dbt tests, source freshness checks, and documentation so downstream consumers can trust what they see - Write complex SQL transformations on large datasets; optimize for cost and performance Reporting &





• BI - Translate business questions into well‑scoped analytical requirements; define metrics in collaboration with Capital leadership and keep definitions governed in our semantic layer - Build and own the Omni BI semantic layer, enabling self‑serve chat and dealer‑facing embedded reporting - Balance responsiveness to ad‑hoc requests while optimizing via building: triage what should be answered once vs. what should be codified so stakeholders or AI tools can self‑serve it in the future - Deliver clear, compelling data narratives to non‑technical stakeholders; support follow‑on questions and iterate quickly Capital Business Domains - Lead Targeting: develop models and dashboards that identify high‑propensity dealer and borrower segments to support outbound sales strategy - Loan Origination Tracking: build funnel visibility from application through funding; surface bottlenecks and conversion opportunities - Operational Functions: provide analytical support for account management workflows, dealer servicing SLAs, and audit/compliance reporting Project Ownership &

• Stakeholder Partnership - Own analytical initiatives end‑to‑end: identify stakeholders, define scope and timelines,



and execute without requiring close supervision - Proactively surface opportunities and deliver data‑driven recommendations — not just answers to questions that were asked - Navigate competing priorities across multiple stakeholder groups; propose win‑win solutions when technical requirements conflict What you will need (Skills, Experience, Education) Education - BA/BS in Statistics, Mathematics, Computer Science, Operations Research, or related - Master's or Ph.D. a plus, but offset by demonstrated experience and a deep toolbox Experience - 5+ years of professional experience in analytics engineering, data engineering, or BI - Hands‑on production experience with dbt (model design, testing, documentation, incremental strategies) - Proficiency building semantic layers

• Omni or Looker BI experience preferred, but similar experience considered - Expert‑level SQL; comfortable with window functions, complex joins, and query optimization in BigQuery or a comparable cloud warehouse - Experience delivering major analytical initiatives independently, from scoping through stakeholder presentation - Background in financial services, fintech, or lending is a meaningful plus - familiarity with origination, account management, or B2B lending workflows accelerates ramp - Experience with Git‑based version control workflows Soft Skills - Communicates analytical findings clearly to non‑technical audiences - Comfortable navigating ambiguity - Collaborative, low‑ego, and invested in the team’s collective output - Solid instinct for knowing when to answer quickly vs. when to build properly Nice‑to‑Haves - Experience with Google Cloud Platform - Familiarity with AI‑assisted analytics or developer workflows - Exposure to credit risk, payment systems, or audit/compliance reporting contexts

📌 Analytics Engineer IV, ACV Capital (Toronto)
🏢 BetterCloud
📍 Toronto