Role Description As our sole Analytics Engineer, you'll be hands-on building and maintaining the data infrastructure that powers Snout — from BI integrations with our veterinary customers to the pipelines and models that make our data reliable and useful. You'll partner closely with teams across GTM, marketing, CX, and engineering to translate business questions into analytics assets that actually get used. Your impact will be felt across the entire organization. The insights and reporting infrastructure you build will directly shape how Snout's clinic partners experience our product and how our internal teams make decisions. This is a foundational role at a critical stage of our growth. If you're someone who loves working with data, thrives in ambiguity, and wants to build something from the ground up, we'd love to hear from you! Qualifications - 5+ years of experience in data analytics, building and maintaining data infrastructure - Experience across data and analytics, reporting/visualizations, data warehousing, data testing, and analytics engineering - A proven track record of data integration for data model consumption - Experience analyzing large datasets from multiple source systems for reporting consumption - Hands-on experience with Looker, dbt, SQL, Snowflake, and Fivetran (or similar) and coding with python (or similar) - Ability to collaborate with various departments in a cross-functional environment to deliver usable insights Requirements - Integrate with our veterinary partners' software to develop data pipelines and dbt models to support Snout's data offering, ensuring our infrastructure reliably delivers data to analytics and business systems - Understand and translate business needs into executable data transformation models that deliver key technology assets across the organization - Provide analytics modeling, data testing, data engineering, and reporting - Create algorithms to determine relationships between various data sources and surface insights for end users - Discover and deliver insights and reporting to our customers and internal stakeholders Benefits - Day 1 medical/dental/vision benefits - Flexible time off + 11 Snout calendar holidays - Paid parental leave

• Design, develop and implement complex ETL processes of healthcare data to meet a wide range of business and system requirements • Support the ETL operational processes including but not limited to: automation, job scheduling, dependencies, monitoring, maintenance, patches, upgrades, security, and administration • Identify process improvements and innovative ways to solve existing or new problems

• Lead the design and delivery of end-to-end analytics solutions, from requirements to deployment and optimization • Ensure analytics products meet Enterprise Operations Insights standards for data modelling, UX design, and storytelling • Drive adoption of AI-ready data practices, ensuring data is structured for scalability and AI consumption • Collaborate closely with Data Engineering to align on architecture, dataflows, and optimized data structures • Actively contribute to building, testing, refining, and improving AI-driven analytics solutions • Drive stakeholder engagement through clear communication, proactive updates, and expectation management

• Implement cost monitoring and alerting solutions across cloud platforms under senior guidance • Develop scripts and automation tools to support cost optimization workflows • Assist in building cost allocation and tagging implementations for accurate cost attribution • Create and maintain cost optimization dashboards and reporting tools • Support integration efforts between cloud billing APIs and internal systems • Contribute to tooling development that supports FinOps processes across product and platform groups • Help implement cost guardrails and automated policies to prevent cost overruns • Assist in developing cost data collection and processing pipelines • Support technical documentation creation for cost-efficient infrastructure patterns • Participate in code reviews and technical design discussions • Monitor and maintain existing cost management tools and systems • Assist in troubleshooting cost-related technical issues • Help implement and test cost optimization recommendations • Support data quality initiatives for cost reporting accuracy • Participate in on-call rotation for cost management systems