Analytics Engineer III, Assurance

ACV Auctions; Toronto; On-site; CAD 110,000 - 150,000; Full time

Job summary

ACV Auctions in Toronto is seeking an Analytics Engineer III on the Assurance team to transform raw data into trusted models and reports, spanning dbt modeling, data quality, and Omni BI dashboards.

You will reduce ad-hoc analytical bottlenecks, surface insights on arbitration risk and product initiatives, and build self-serve analytics with AI-assisted querying for business stakeholders.

Qualifications

• BA/BS in Statistics, Mathematics, CS, OR or related field.
• Master's or PhD is a plus, offset by experience.
• 3+ years in analytics engineering, data engineering, or BI.
• Hands-on dbt production experience.
• Expert SQL with complex joins and window functions.

Responsibilities

• Design, build, and maintain dbt models serving as truth for KPIs.
• Translate business questions into analytical requirements and define metrics.
• Build on Omni BI semantic layer for self-serve reporting and AI-assisted querying.
• Deliver data-driven recommendations and support stakeholders.
• Collaborate with Assurance Business to surface insights on arbitration risk.

Skills

SQL

dbt

Data modeling

BI / dashboards

Git / version control

Communication

Problem solving

Education

BA/BS in Statistics, Mathematics, CS, OR

Master's or PhD a plus

Tools

dbt

Looker Omni BI

Google Cloud Platform

BigQuery

Git

Job description

What you will do:

The Analytics Engineer III on the ACV Assurance team is a skilled practitioner who transforms raw data into trusted, decision-ready models and reports that drive the business forward. Sitting at the intersection of data engineering and business intelligence, this role contributes across the full analytics stack - from dbt model design and data quality to Omni BI dashboards - and partners with the Assurance Business to surface insights on arbitration risk and product initiatives.

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 business stakeholders can answer common questions themselves.

Analytics Modeling & Data Quality

• Design, build, and maintain dbt models (staging, intermediate, production layers) that serve as the single source of truth for Assurance 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 Assurance stakeholders and keep definitions governed in our semantic layer
• Build upon our 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

Assurance Business Domains

• Risk: support the business in developing data, predictive, and forecasting models that identify high-risk dealer and vehicle populations to support program management strategy
• Product: develop dealer-facing dashboards that illustrate their arbitration trends over time

Project Ownership & Stakeholder Partnership

• Execute scoped projects with general guidance: define approach and timelines with input from a manager or senior team member, and drive day-to-day execution independently
• Deliver data-driven recommendations
• Navigate competing priorities across multiple stakeholder groups; propose win-win solutions when technical requirements conflict

What you will need:

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

• 3+ years of professional experience in analytics engineering, data engineering, or BI
• Hands-on production experience with dbt (model design, testing, documentation, incremental strategies)
• Expert-level SQL; comfortable with window functions, complex joins, and query optimization in BigQuery or a comparable cloud warehouse
• Experience delivering analytical initiatives independently, from scoping through stakeholder presentation
• Experience with Git-based version control workflows

Soft Skills

• Excellent communicator with a strong attention to detail; genuinely curious about the business and willing to dig into the specifics to get things right
• Collaborative, low-ego, and invested in the team's collective output
• Strong instinct for knowing when to answer quickly vs. when to build properly
• Communicates analytical findings clearly to non-technical audiences
• Comfortable navigating ambiguity

Nice-to-Haves

• Proficiency building semantic layers; Omni or Looker BI experience preferred, but similar experience considered
• Experience with Google Cloud Platform
• Familiarity with AI-assisted analytics or developer workflows
• Experience with binary classification and/or loss forecasting

#LI-AM3