We are looking for an experienced Analytics Engineer to own and evolve the BI team’s technical infrastructure (Snowflake, dbt, GitLab CI/CD, scheduling frameworks, and ingestion tooling) while ensuring all BI systems and workflows remain fully aligned with the broader Data Engineering architecture and design principles. This role is responsible for keeping the BI environment scalable, maintainable, and consistent with the company’s overall data platform strategy. You will collaborate closely with Data Engineering, who manage the source-to-mesh pipelines, and build everything needed to deliver clean, reliable, analytics-ready data into the BI workspace. This includes developing curated data layers, ensuring pipeline reliability, maintaining governance standards, and enabling efficient downstream analytics across dashboards, reporting, and domain models. Why “Analytics” Engineer? This role is intentionally scoped as an Analytics Engineer, not just a data or platform engineer because success requires: Understanding analytics use cases, business metrics, and performance KPIs Designing data models that correctly support those metrics and semantic definitions Working closely with business stakeholders to gather context and ensure data structures reflect real-world logic Balancing technical efficiency with analytical usability, building data assets that analysts and business teams can reliably use for decision-making You will serve as the bridge between technical data systems and the analytical needs of the business.