Senior Analytics Engineer, Marketing

instacart· 152 open roles

Remote RemoteFull-time2 weeks ago

Salary

$191,000 - $201,500

Experience

Mid

Job Type

Full-time

Posted

2 weeks ago

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About This RoleAI processing…

We're transforming the grocery industry

At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers.

Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.

Key Responsibilities

1
Analytics Data Modeling: 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
Cross-functional Partnership: 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
Metrics & Definitions Ownership: Lead efforts in metric definition, business logic standardization, testing, and documentation to ensure consistent, trusted reporting across marketing.
4
Technical Leadership: 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
Model Evolution & Optimization: Continuously improve existing data models to reduce complexity, improve query performance, and increase analyst self-service capabilities.
6
Scalable Analytics Infrastructure: Develop scalable analytics engineering patterns, including dimensional models, semantic layers, testing frameworks, and monitoring approaches, to support evolving marketing measurement needs.
7
AI & ML Enablement: Partner with Data Scientists & Analysts to build and maintain curated datasets that provide context for ML & AI-driven marketing applications.

Requirements

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.
Experience building or contributing to a metrics/semantic layer.
Familiarity with BI tools (Looker, Tableau, Hex, etc.) and optimizing models for analyst consumption.
Experience working directly with Data Scientists on experimentation, attribution, or incrementality measurement.
Familiarity with marketing platforms (e.g., Google Ads, Meta, Google Analytics, SEO tooling).
Python experience for automation or advanced transformations.
Experience introducing analytics engineering best practices in an organization that didn't previously have them.