Tribeca Venture Partners is seeking a Senior Analytics Engineer on the ACV Capital team who will transform raw data into trusted, decision-ready models and reports. This role involves owning the full analytics stack and partnering with Capital leadership to surface insights on various business domains while reducing analytical bottlenecks.
Responsibilities:
- 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
- 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
- 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
- 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
Requirements:
- BA/BS in Statistics, Mathematics, Computer Science, Operations Research, or related
- 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
- 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
- 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
- Master's or Ph.D. a plus, but offset by demonstrated experience and a deep toolbox
- Omni or Looker BI experience preferred, but similar experience considered
- Experience with Google Cloud Platform
- Familiarity with AI-assisted analytics or developer workflows
- Exposure to credit risk, payment systems, or audit/compliance reporting contexts