BI & Revenue Operations Lead

Vendasta•Corman Park No. 344, SK

2d•Remote

About The Position

Vendasta is seeking an AI-first BI & Revenue Operations Lead to own and elevate our cross-functional data, analytics, and financial modeling ecosystem. This is a forward-thinking role that blends modern AI tooling - including Claude and other LLM-based assistants - with classical BI rigor to give Vendasta a single, trusted, and predictive view of the business. This role sits at the intersection of GTM, Finance, and Product. It depends on tight collaboration with our centralized Data Engineering team for trusted data assets, with source system owners (Vendasta CRM, billing, product telemetry, HRIS, etc.) to fix upstream processes and definitions, and with executives whose direction shapes the questions BI must answer. The Lead will operate as both a player and a coach. You will be hands-on querying data, building automated revenue forecasting and commission models, and using AI to dramatically compress the time from question to insight - while upskilling a high performing BI function that serves as Vendasta's single source of truth. The Three Dimensions of Your Impact include Business Intelligence: Building the visualization, querying, and reporting layer - augmented by AI - that empowers stakeholders to track performance in real time and self-serve insights. Revenue Forecasting: Developing predictive models - leveraging AI assistance for hypothesis generation, anomaly detection, and narrative - to anticipate revenue trends, churn, and growth trajectories. Commission Planning: Modeling and auditing data-driven incentive structures that align sales behavior with company goals.

Requirements

8+ years in BI, Data Analytics, Revenue Operations, or Financial Planning & Analysis (FP&A).
Strong, demonstrable SQL skills - you can write, read, and optimize queries against a real warehouse without waiting on someone else.
Active, daily use of AI assistants such as Claude for analytics workflows - SQL drafting, data exploration, report writing, code review. You can articulate where AI accelerates the work and where it must not be trusted.
Proficiency with data modeling and BI tools such as Looker, Power BI, or Tableau.
Proven experience building or auditing financial models and commission structures.
Deep understanding of SaaS metrics (ARR, NRR, CAC, LTV) and GTM systems like Salesforce or HubSpot.
Track record of working effectively with Data Engineering, source system owners, and executives - not in a silo.
A systems thinker who can balance hands-on technical work with high-level strategic planning.

Responsibilities

Serve as the primary BI partner for Sales, Marketing, Finance, and Product to align analytics with organizational goals.
Act as the connective tissue between business stakeholders and the centralized Data Engineering team - identifying, escalating, and prioritizing new data requirements.
Partner with source system owners (Salesforce, billing, product, HRIS, support) to fix upstream definitions, data quality, and process - BI cannot be trusted if the source isn't.
Secure and protect recurring executive time to direct BI's roadmap, validate priorities, and pressure-test outputs.
Establish BI governance, documentation, metric definitions, and best practices to ensure data accuracy across all reporting surfaces.
Open the organization to a trusted self-serve model - gold-standard executive dashboards on one end, AI-assisted ad-hoc querying for the broader org on the other.
Be hands-on with SQL: write, optimize, and review queries directly against the data warehouse - this is a player role, not just a coach role.
Use Claude and other AI tools as a daily co-worker - for SQL generation and review, data exploration, narrative writing, anomaly investigation, and turning raw outputs into executive-ready reports.
Build AI-augmented workflows that cut the time from executive question to defensible answer (e.g., natural-language-to-SQL on governed schemas, automated weekly business reviews, AI-drafted commentary on variance).
Embrace and evaluate new AI tooling continuously; bring a point of view on what to adopt, what to wait on, and what to build internally - consistent with Vendasta's AI-first operating principle.
Apply Vendasta's trust-by-design AI principles: keep humans in the loop on high-stakes outputs (forecasts, commissions, board-level numbers), document model assumptions, and validate against ground truth.
Partner with the VP, Revenue Operations to support revenue strategy through advanced forecasting, pipeline visibility, and multi-quarter revenue walks.
Build baselines, trend models, and churn/retention models that produce predictable revenue - not just historical reporting.
Conduct deep-dive analyses (often AI-accelerated) to uncover insights that drive Net Retention Revenue (NRR) and customer lifecycle optimization.
Translate findings into written reports and executive narratives - not just dashboards.
Own the data architecture behind sales commission structures, ensuring calculations are automated, transparent, and auditable.
Analyze the effectiveness of current commission plans and provide data-backed recommendations for adjustments.
Develop standardized KPI frameworks that link individual performance directly to financial payouts.
Define the long-term vision for the BI and Revenue Analytics function, including team structure, AI tooling stack, and ways of working.
Mentor and eventually lead a growing team of analysts; raise the bar on AI fluency across the team.
Champion a data-driven, AI-assisted culture - translating complex financial and technical data into actionable insights for non-technical leaders.