The 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
• Strong 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

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Our Values

Trust & Transparency | People First | Positive Experiences | Calm Persistence | Never Settling

Compensation: The compensation range for this position is listed in the "Job Details" section at the bottom of this posting. Please note that final compensation will be determined based upon the applicant's relevant experience, skill set, location, business needs, market demands, and other factors as permitted by law.