Description
We are seeking a Principal Analytics Engineer to lead the design and build of our AI-powered intelligence system. This role involves synthesizing complex data streams into a unified, high-fidelity system that serves as the 'source of truth' for the entire customer journey. You will engineer a structured knowledge layer that enables us to scale Go-To-Market (GTM) efforts in a world where data must be optimized for human reporting, predictive science, and conversational AI alike.
Key responsibilities include:
Architecting the foundation: designing and building the core BigQuery and dbt infrastructure that powers our marketing intelligence, transforming raw signals into high-fidelity, agent-ready data products.
Enabling AI & Agents: developing the semantic layer and structured knowledge base that allows AI agents to accurately 'talk' to our business data and reason through complex performance questions.
Mapping the journey: integrating disparate signals across digital, product, and sales into a unified lifecycle model that tracks the customer's path from discovery to revenue.
Scaling through partnerships: partnering with Enterprise, Product, Sales, and Finance teams to align on shared metrics while mentoring other engineers to uphold high standards for our data foundation.
Requirements include:
Deep experience with BigQuery, dbt, and semantic layers.
Ability to build complex, interconnected systems by starting with the desired outcome and working backward.
Systems & Design Thinking: the ability to look at a complex web of data and see the underlying architecture required to make it simple and extensible.
Collaborative Communication: a track record of 'translating' technical debt into business value and coaching peers through complex architectural hurdles.
Operational Excellence & Governance: treating data as infrastructure and having deep experience implementing data contracts, automated quality monitoring (DQM), and governance frameworks.