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Job Description
📋 Description Build and maintain data models and pipelines that deliver well-defined, tested, and documented data Contribute to data quality standards, model documentation, and column-level lineage across our dbt Support the team in pushing data into business operating systems and AI-powered workflows that help Learn and apply best practices around source-of-truth models, metric definitions, and data grain Use AI to automate analytics engineering processes, reduce toil, and build net-new capabilities for Partner with data platform engineers to help ensure pipelines and data models run reliably in 🎯 Requirements Experience: 1–2 years as an analytics engineer, data analyst, or in a related technical role dbt & SQL: Foundational SQL skills and some exposure to dbt or a modern data stack; a strong AI fluency: Curiosity about using AI to move faster, automate processes, and build things that Technical skills: Some familiarity with Python and an eagerness to grow. Basic understanding of Business judgment: Interest in understanding how data models serve real business decisions, and how Semantic precision: Care for writing clear, unambiguous definitions and documentation, for both 🎁 Benefits Competitive salary with pay transparency Remote-friendly, distributed team Equal Opportunity employer; inclusive hiring
