Senior Analytics Engineer, Marketing

Instacart Instacart · Consumer · United States · Remote · Marketing

Instacart is seeking a Senior Analytics Engineer to own and evolve the marketing analytics data foundation. This role involves designing, building, and maintaining data models using dbt, partnering with Data Scientists and Analysts, and providing technical leadership in analytics engineering best practices. The role will also support ML & AI-driven marketing applications by building curated datasets.

What you'd actually do

  1. Design, build, and maintain high-quality dimensional and semantic data models using dbt that support marketing analytics across Paid Marketing, SEO, Retailer Marketing, and attribution.
  2. Work closely with Data Scientists, Analysts, and Marketing stakeholders to understand analytical needs, translate business questions into data requirements, and deliver trusted, decision-ready data assets.
  3. Lead efforts in metric definition, business logic standardization, testing, and documentation to ensure consistent, trusted reporting across marketing.
  4. Set standards for analytics engineering best practices—including code review, testing frameworks, and modeling patterns—to ensure scalability, reliability, and maintainability across the marketing data ecosystem.
  5. Continuously improve existing data models to reduce complexity, improve query performance, and increase analyst self-service capabilities.

Skills

Required

  • Analytics Engineering
  • SQL
  • dbt
  • Snowflake
  • marketing data and metrics
  • analytics engineering best practices

Nice to have

  • metrics/semantic layer
  • BI tools (Looker, Tableau, Hex)
  • Data Scientists on experimentation, attribution, or incrementality measurement
  • marketing platforms (Google Ads, Meta, Google Analytics, SEO tooling)
  • Python
  • introducing analytics engineering best practices

What the JD emphasized

  • 5+ years of experience in Analytics Engineering or a closely 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, including paid media performance, attribution concepts, and channel-level measurement
  • Demonstrated ability to set standards, guide execution, and mentor others on analytics engineering best practices
  • Excellent judgment and product thinking—you know how to balance speed, correctness, and long-term maintainability