Senior Analytics Engineer, Marketing

Role Overview

Senior Analytics Engineer position within the Marketing Enablement & Technology (MET) team, reporting to the Marketing organization. You will own and evolve the marketing analytics data foundation, designing high-quality data models and providing technical leadership across marketing data modeling.

Key Responsibilities

• Analytics Data Modeling: Design, build, and maintain high-quality dimensional and semantic data models using dbt supporting Paid Marketing, SEO, Retailer Marketing, and attribution
• Cross-functional Partnership: Work closely with Data Scientists, Analysts, and Marketing stakeholders to understand analytical needs and deliver decision-ready data assets
• Metrics & Definitions Ownership: Lead efforts in metric definition, business logic standardization, testing, and documentation for consistent reporting across marketing
• Technical Leadership: Set standards for analytics engineering best practices including code review, testing frameworks, and modeling patterns
• Model Evolution & Optimization: Continuously improve existing data models to reduce complexity, improve query performance, and increase analyst self-service capabilities
• Scalable Analytics Infrastructure: Develop scalable analytics engineering patterns including dimensional models, semantic layers, testing frameworks, and monitoring approaches
• AI & ML Enablement: Partner with Data Scientists to build curated datasets for ML and AI-driven marketing applications

Requirements

• 5+ years of experience in Analytics Engineering or related role with ownership of production-grade analytical data models
• Expert-level SQL skills and deep experience designing dimensional models (star schemas, fact/dimension tables, SCDs)
• Strong proficiency with dbt, including project structure, testing, documentation, and macros
• Experience with Snowflake or similar cloud data warehouses
• Solid understanding of marketing data and metrics (paid media performance, attribution concepts, channel-level measurement)
• Demonstrated ability to set standards, guide execution, and mentor others on analytics engineering best practices
• Excellent communication skills