Staff Analytics Engineer

Engine is transforming business travel into a personalized and rewarding experience. As a Staff Analytics Engineer, you will lead the transition to a sophisticated data architecture and define engineering standards to enhance the efficiency of the data organization.

Responsibilities:

• Lead the design and execution of a massive migration from 1,200+ legacy dbt models into a modular, three-project Medallion structure (Bronze, Silver, Gold)
• Define the 'Engine Standard' for data contracts, naming conventions, and testing frameworks
• Partner with the Principal Engineer to optimize our Snowflake footprint
• Identify systemic inefficiencies in our DAGs and warehouse usage to drive down costs while increasing query speed
• Act as a force multiplier for the team by leading high-level design reviews and providing 'Staff-level' feedback on PRs
• Bridge the gap between Engineering and Business to ensure our infrastructure supports long-term growth without compromising day-to-day execution speed

Requirements:

• Expert-Level dbt Mastery: You don't just 'use' dbt; you understand dbt Mesh, cross-project dependencies, and how to refactor massive projects without breaking downstream BI tools like Looker
• Legacy Refactoring Experience: 8+ years of industry experience with a proven track record of migrating large-scale, 'messy' data environments into clean, governed architectures
• The 'Engineer' in Analytics Engineer: Deep proficiency in Python for data operations, Airflow for orchestration, and a rigorous approach to Version Control and CI/CD
• Architectural Vision: Ability to look at 1,200 models and see the patterns. You prefer simple, elegant abstractions over complex, brittle 'quick fixes.'
• Influence without Authority: You can articulate technical debt and architectural trade-offs to stakeholders, gaining buy-in for long-term infrastructure health