Analytics Engineer III, Assurance

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