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

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