• Set the direction Own the long term direction of the Intelligence offering, spanning data models, analytics, and customer facing insights. • Partner with Product to build a roadmap for our data science offerings. • Provide insights and what-if analysis tooling for our C-Suite customers. • Establish the architectural principles, analytical standards, and ways of working that allow Intelligence to scale safely and credibly. • Design and evolve the data architecture and canonical data model that underpins Intelligence, building on an existing warehouse. • Develop and ship data science work: predictive signals, pattern detection, automated insights: that genuinely moves the needle for customers. • Design and deliver dashboards that customers trust and rely on. • Own analytics engineering end to end: modelling data, optimizing queries, versioning work, and reviewing changes before they reach customers. • Introduce tooling and processes that speed up development while improving quality and consistency. • Work hand in hand with Engineering to ship Intelligence features into the product. • Engage directly with customers to understand reporting needs, explain insights, and validate value. • Support Commercial and Operations teams with insights that underpin upsell, renewal, and confident decision making.

• Own the architecture and governance of Thistle’s end-to-end data infrastructure, ensuring scalability, reliability, and adherence to best practices • Lead the design and implementation of our core data models and pipelines (ETL/ELT), enabling advanced analytics, reporting, and experimentation • Drive cross-functional alignment on data definitions, metrics, and source-of-truth models to ensure consistency and clarity across teams • Develop and mentor analytics engineers and analysts, elevating technical standards and fostering a data-driven mindset throughout the company • Serve as a strategic partner to senior leadership by identifying opportunities for data to unlock business value and advising on high-impact initiatives • Continuously optimize the performance of our data warehouse (e.g., Snowflake, BigQuery, or Redshift), workflows, and query efficiency • Champion best-in-class tooling and practices, including dbt, Airflow, version control, testing frameworks, and documentation standards • Support self-serve analytics by building scalable, intuitive data products, dashboards, and exploration tools tailored to business stakeholders.

• End-to-end ownership of data platform and BI layer • Contribute to a zero-waste future by reducing food waste and emissions • Evolve vendor-built BI solution into a modern data platform • Design and operate scalable pipelines and lakehouse architecture • Build and maintain customer-facing dashboards and embedded analytics • Define standards, data contracts, and architecture principles

• Lead the design, development, testing, and deployment of local and enterprise-level data models for analytics solutions. • Build and maintain ETL pipelines across multiple data sources and application ecosystems. • Optimize data models and query performance for efficiency, scalability, and maintainability. • Develop and monitor data quality dashboards, ensuring data accuracy and integrity. • Design, develop, test, and deploy interactive dashboards, reports, metrics, apps, and workspace objects using Power BI. • Build advanced analytics products such as forecasting models, prescriptive analytics, and sentiment analysis solutions. • Create and maintain data catalogs and monitoring frameworks for analytics assets. • Design and implement secure data access models, including dynamic Row-Level Security (RLS). • Develop protocols for seamless user access management and BI governance. • Collaborate on data-sharing policies, standards, and integration strategies. • Work closely with Solution Architects, Product Owners, and stakeholders to gather requirements and translate them into scalable analytics solutions. • Apply UI/UX best practices and analytics design principles in product development. • Facilitate demos, user acceptance testing (UAT), training sessions, and post-deployment hypercare support. • Participate in Agile delivery practices and contribute to continuous improvement initiatives.