Principal Analytics Engineer

Elastic Elastic · Enterprise · United States · Marketing Operations

This role is for a Principal Analytics Engineer to lead the design and build of an AI-powered intelligence system for the Marketing organization. The focus is on creating a semantic blueprint for business data, transforming raw signals into high-fidelity, agent-ready data products, and enabling AI agents to interact with this data. The role involves architecting BigQuery and dbt infrastructure, mapping the customer journey, and partnering with various teams.

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
  • AI production scaling
  • agentic workflows

What the JD emphasized

  • agent-ready data products
  • AI agents
  • LLM-assisted workflows
  • data contracts

Other signals

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