Principal Analytics Engineer

Elastic Elastic · Enterprise · United States · Marketing Operations

The Principal Analytics Engineer will lead the design and build of an AI-powered intelligence system for the marketing organization, creating a semantic blueprint for business data interaction. This role involves architecting BigQuery and dbt infrastructure, developing a semantic layer for AI agents, and integrating disparate data signals into a unified customer journey model.

What you'd actually do

  1. Architect the Foundation: Design and build the core BigQuery and dbt infrastructure that powers Elastic’s marketing intelligence, transforming raw signals into high-fidelity, agent-ready data products.
  2. Enable AI & Agents: Develop the semantic layer and structured knowledge base that allows AI agents to accurately "talk" to our business data and reason through complex performance questions.
  3. Map the Journey: Integrate disparate signals across digital, product, and sales into a unified lifecycle model that tracks the customer’s path from discovery to revenue.
  4. Scale through Partnerships: Partner with Enterprise, Product, Sales, and Finance teams to align on shared metrics while mentoring other engineers to uphold high standards for our data foundation.

Skills

Required

  • BigQuery
  • dbt
  • semantic layers
  • data contracts
  • automated quality monitoring (DQM)
  • governance frameworks

Nice to have

  • Go-To-Market (GTM) mechanics
  • Marketing Mix Modeling (MMM)
  • causality
  • incrementality analysis
  • GDPR/CCPA compliance
  • Identity Stitching
  • Customer 360 frameworks

What the JD emphasized

  • agent-ready data products
  • human teammates and AI agents
  • LLM-assisted workflows
  • data contracts
  • agentic workflows

Other signals

  • AI-powered intelligence system
  • agent-ready data products
  • AI agents to accurately "talk" to our business data
  • LLM-assisted workflows