Senior Data Engineer (Analytics)

- Cross-Functional Collaboration: Experience working with Data Scientists, ML Engineers, analysts, and business stakeholders to understand requirements and deliver reliable data products - Analytics Engineering Fundamentals: Strong SQL skills and experience designing dimensional data models, defining business metrics, and building datasets that support complex analytical questions - Semantic Modeling: Understanding of semantic layers, metric definitions, and how to structure data so that business logic is reusable, consistent, and interpretable across multiple datasets - AI-Native Development: Experience using agentic coding tools (Cursor, Codex, Claude Code or similar) as a core part of your daily work - Data Engineering Experience: Experience turning raw, high-volume event data into reliable production datasets, including applying business logic, building and maintaining transformations, and validating data quality in a modern cloud warehouse with orchestration tools like Airflow - Have experience working with Snowflake, Airflow, dbt, or comparable data transformation and orchestration technologies - Enjoy taking ownership of ambiguous problems, working directly with stakeholders, and building solutions that have measurable business impact - Are interested in how LLMs and AI agents can transform the way organizations discover, understand, and analyze data - Have built or contributed to semantic layers using tools such as Looker, dbt Semantic Layer, or similar frameworks…