Analytics Engineer

The Role

Transform how an organization interacts with its data by building the foundational models that drive enterprise decision-making. In this position, you'll act as the bridge between raw data and actionable strategy, collaborating with departments like Product and Finance to create scalable, high-quality analytics structures. You aren't just writing queries; you are solving business puzzles and hardening data pipelines through advanced testing and automation.

Technical Ecosystem

This environment is built for developers who think in systems. You will work extensively with a modern data stack including Snowflake, dbt, and Python. Because the team emphasizes modularity and 'agentic' approaches, it is a perfect fit for engineers who use AI tools to handle the heavy lifting of SQL boilerplate and Jinja templating. You’ll manage the entire lifecycle from Jupyter Notebook experimentation to production-grade CI/CD deployments.

What You'll Achieve

• Architect Scalable Models: Use dbt and SQL to build clean, modular data layers that serve as the backbone for company-wide reporting.
• Drive AI Innovation: Leverage an AI-forward culture to explore agentic workflows and automated dataops.
• Strategic Partnership: Work directly with stakeholders to design custom analytics solutions that solve complex operational challenges.
• Continuous Improvement: Replace manual processes with automated systems, ensuring data freshness and accuracy through rigorous testing.