Analytics Engineer

Analytics Engineer (US Only) #2987 About the Role One of our Partners is looking for an Analytics Engineer to join their growing team. In this role, you will sit at the intersection of business strategy and data engineering, serving as the engine that powers our data infrastructure and shapes our long-term data strategy .Operationally, you will own the development and maintenance of our data pipeline using dbt Cloud and BigQuery, transforming raw data into clean, production-grade models that empower our analysts and business users. Strategically, you will act as a key partner to the Data & Analytics Manager, helping to evaluate modern BI tools, design a self-service data platform roadmap, and transition our capabilities from historical reporting into proactive forecasting and trend analysis . Most Important • Mastery of complex SQL (CTEs, window functions, schema design, and query optimization) to build and maintain clean, reliable data structures • Hands-on experience with dbt Cloud, including building, testing, debugging, and monitoring scheduled jobs daily • Professional experience working within Google BigQuery • Proficiency with Git workflows, including managing pull requests, code reviews, and branching strategies for data model changes • A track record of monitoring data quality, resolving pipeline failures under tight timelines, and handling service desk/ad-hoc support requests for stakeholders Nice to Have • Familiarity evaluating or working with platforms like Tableau, Sigma, Omni, or Metabase • Experience transitioning an organization from a request-driven data model to a self-service data platform architecture. • Familiarity with predictive techniques, statistical modeling, or the tools required to move from historical reporting to proactive forecasting and trend analysis • Experience with team capacity planning, competency mapping, or assisting in building a workforce roadmap for a scaling data function. Personal Traits • You have a sharp eye for detail, a passion for data quality, and a structured approach to debugging and solving complex data logic. • You don't just execute tasks; you look at the bigger picture, think about scalability, and love contributing to roadmaps and vendor evaluations. • You can seamlessly shift gears between deep-focus project work (like designing a new dbt model) and fast-paced operational needs (like resolving a failing job or an urgent manager ad-hoc reqquests) • You can bridge the gap between technical execution and business needs, whether you are writing audit documentation for stakeholders or collaborating on cross-functional requirements.