- Own **ad-hoc reporting and analysis** for operations, finance, and leadership - Build and maintain **Power BI dashboards and reports** - Translate ambiguous business questions into clear analytical outputs - Partner with stakeholders to define and refine KPIs and metrics - Ensure reporting is accurate, performant, and trusted **SQL & Data Modeling** - Write high-quality SQL to support reporting and analytics - Build and improve **analytics-ready (gold-layer) datasets** - Contribute to dimensional and fact-based data models - Help improve consistency, usability, and documentation of core datasets **Growth & Technical Evolution** - Gradually take on more responsibility in data modeling and analytics engineering - Collaborate on improving analytics architecture and best practices - Explore advanced analytics or ML use cases over time (as interest and readiness allow)

• Drive the implementation and continuous improvement of our data connections, analytics best practices, and ETL processes. • Centralize the Company’s cloud data into Snowflake and facilitate modeling to support data analysis requirements from all functional groups of the company and its clients. • Create a common data framework and glossary so all company and client data can be analyzed in a unified manner. • Work with the product, operations, and executive management teams to create a data- enabled user and client roadmap that clearly defines roles and responsibilities while bringing all teams into our collaborative data programs. • Collaborate with Sales, Marketing and Services leadership to support our external client base needs. • Create and execute a plan to develop and mature our ability to measure and optimize usage growth, aligned with our user and client roadmap. • Ensure all transactional systems can communicate with our modern data tech stack and that production data adheres to a unified data model. • Collaborate with all functions of the company to address data needs and make required data available to analysts and end-users. • Build a multi-modal service model that meets the non-homogeneous needs of our functional groups, from full service to self service, across our data stack.

• Act as a SME in Analytics Engineering, BI, and data domain to support enterprise business needs • Mentor and advise Analytics Engineering team members • Drive the design of highly complex data models and BI applications • Select appropriate data and BI tools and technologies to implement solutions • Leverage advanced experience in Analytics Engineering within an Agile team • Contribute to the management of a portfolio of programs • Support production processes and advise team on troubleshooting and resolutions • Train engineering teammates in coding, data modeling, and BI development best practices • Discuss and recommend advanced and innovative data and BI solutions • Explore and develop detailed understanding of external developments or emerging issues

• Build workflow automations in n8n, developing modular, reusable sub workflows and scalable patterns • Integrate with internal and external APIs, handling authentication, error recovery, retries, rate limits, and tolerant connectivity patterns • Build and refine agentic workflows using LLMs, including guardrails, safe failure modes, and input validation • Monitor and troubleshoot workflow executions across APIs, agentic behaviour, data transformations, and orchestration layers • Break down ambiguous requests into scoped work packages, prototypes, and MVPs • Own workflows end to end, from concept to deployment to ongoing monitoring