• Lead and grow a team of analytics engineers (currently 2, scaling to 4 this year), building a culture of craft, documentation, and user empathy • Drive the rollout and adoption of Lightdash as our single source of truth for business reporting, based on a unified KPI framework currently in progress • Own all dashboard development initially - from executive reporting to operational views, with support from analysts - then fully transition the ownership to analysts as self-service matures, building the templates and processes that enable this shift • Partner with stakeholders to translate reporting needs into well-designed, maintainable data products • Design and deliver training and enablement programs for business users across all functions • Own and evolve our core dbt models and semantic layer to support key analytical use cases: customer LTV, acquisition effectiveness, retention, funnel performance, and financial reporting • Establish governance and standards: metric definitions, dashboard design patterns, modeling practices, testing frameworks, and documentation • Partner with analysts to translate their needs into scalable data assets, and with Data Engineering on pipeline reliability and data quality • Partner with Data Engineering on pipeline reliability, data quality, and infrastructure decisions • Balance rigour with delivery speed-we're still building foundations while the business moves fast

• Design and maintain the canonical revenue and subscription data model, centered on Stripe • Model subscription lifecycles including upgrades, downgrades, renewals, cancellations, refunds, and disputes • Implement ARR, MRR, NRR, churn, and customer/account counts as tested, versioned dbt models • Partner with Finance to translate business definitions into precise, production-grade SQL logic • Build and maintain reconciliation logic between dbt models, Stripe, and Finance-owned reports • Investigate and resolve discrepancies surfaced during reconciliation and downstream use • Own the technical correctness of revenue numbers used in executive and external reporting • Own data quality for all revenue and financial models, including test coverage and issue investigation • Ensure revenue models adhere to Analytics Engineering standards for documentation, lineage, ownership, and catalog synchronization • Participate in governed change workflows for critical revenue assets, ensuring changes are reviewed, traceable, and auditable • Apply sound engineering judgment when balancing correctness, reliability, and delivery speed • Establish a durable revenue and KPI foundation in the near term • As the foundation stabilizes, improve performance, maintainability, and usability of revenue models • Over time, support forecasting, cohort analysis, and advanced revenue analytics, and contribute revenue-domain expertise to broader Analytics Engineering initiatives • Work closely with Finance as the technical owner of revenue modeling • Coordinate with Data Engineering on ingestion, backfills, and schema changes across Stripe and other revenue-related source systems • Support BI and Analytics teams to ensure revenue models are usable and performant

• Own the input layer to our data platform • Evolve our core data models to support emerging use cases • Automate data flows, and layer in monitoring, alerting, and data quality tests to ensure data is accurate and up-to-date • Work collaboratively across the entire Vanna team to design and implement core clinical, operational, financial, and product KPIs • Build out our reporting and dashboarding layer in support of self-service analytics • Conduct ad-hoc analyses for internal stakeholders and clients, and present findings in a way that drives maximum impact

• Architect, build and optimize robust data models in dbt to power business reporting processes and analytics use cases • Effectively speak with, and listen to, business stakeholders, engineers, designers, executives, etc., so that you can understand business context and support analysts/business stakeholders across GTM, Finance, and Product to design and build single-source-of-truth data assets to drive Vouch’s business • Act as a liaison between Engineering and Analytics to define source and target fields for data assets • Partner with upstream Engineering teams to develop new and adapt existing data models as our technology and business evolve • Clearly document specs and data models with source, description, and field definitions to enhance collaboration, scalability, and usability • Set up tests to ensure data quality, monitor daily job execution, and diagnose/fix issues to ensure SLAs are met • Perform root cause analysis for data quality issues, and partner with upstream teams and business stakeholders to rectify dirty, incomplete, or unreliable data • Maintain and enforce consistent data modelling standards, best practices, and design patterns • Provide and receive constructive feedback through code reviews, technical specifications, and pair programming sessions • Use software development best practices with a focus on version control, testing, reliability and maintainability • Work in dbt, SQL, Snowflake, git, Airflow, Python, Stitch, Mode, and we welcome new ideas!