Senior Data Analytics Engineer, Envoy

• 5+ years of experience in Analytics Engineering, Data Science, or Data Engineering, with a strong track record in high-growth startups
• Mastery of dbt & SQL: You write "software-grade" SQL and have managed complex, large-scale dbt projects
• Python & AI Literacy: Proficient in Python for building ML workflows and interacting with LLM APIs and Vector Databases
• Engineering Discipline: Hands-on experience with modern engineering workflows, including Git, CI/CD, and automated data testing
• An AI-First Builder: You are a practitioner of "vibe-coding"—leveraging LLMs to accelerate development and automate boilerplate—while maintaining the "Human-at-the-Lead" judgment to ensure system integrity
• A Product Thinker: You treat data as a product. You understand that your work is only as good as the decisions it enables for PMs and the efficiency it provides for AI agents
• A Lifelong Learner: You live to learn new things and stay up to date on new technologies and techniques. You are inspired by what people know inside and outside the company and are eager to incorporate that knowledge into your work
• Proactive & Autonomous: You don’t wait for a ticket to fix a bottleneck or a flawed data model. You look for problems and inefficiencies and find elegant solutions before they become major issues
• Emotionally Mature & Humble: You care about being effective over being right. You thrive in a high-standards environment where feedback is a gift

Desirable

• We are a top-notch data organization with a high bar for our code, systems, practices, and people
• At Envoy, we don’t just "report" on data; we build the engine of the company
• As a Senior Analytics Engineer, you are a "Full-stack" Data IC
• You will treat our data assets as products—shipping reliable, high-quality data software
• You will help build our Intelligence Platform, leveraging the power of our Semantic Layer, RAG, and MCP, to enable agentic self-service insights and autonomous intelligence
• You'll also be a key partner to Product Teams, helping guide prioritization and feature development efforts by turning data into a strategic advantage
• We have a modern data stack that includes Redshift, Databricks, dbt, Airflow, Omni, Segment, and Estuary
• Develop the Intelligence Platform: Help build and scale our semantic layer and RAG infrastructure, ensuring our data is modeled for both human consumption and autonomous agentic workflows
• Guide Product Strategy: Partner closely with Product teams to drive prioritization and feature development through deep-dive analysis, KPI definition, and robust data modeling
• Support ML & Data Science Workflows: Build and maintain the data pipelines and feature sets required for machine learning models and advanced data science projects
• Champion Engineering Rigor: Lead the team in applying software engineering best practices, including version control, CI/CD pipelines, and rigorous peer reviews
• Mentor and Multiply: Act as a technical resource for the team, providing guidance on solution design and raising the bar for code quality and architectural intuition