Analytics Engineer II

instacart· 41 open roles

Remote RemoteFull-time2 weeks ago

Salary

CA$139,000 - CA$146,500

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
Marketing Analytics Data Development: Independently build and maintain high-quality dimensional data models and ETL pipelines that support marketing analytics across Paid Marketing, SEO, Retailer Marketing, and attribution — delivering complete data assets end-to-end with minimal oversight.
2
Cross-functional Partnership: Work closely with Data Scientists, Analysts, and Marketing stakeholders to translate analytical needs and business questions into data requirements, and deliver trusted, decision-ready datasets.
3
Data Quality Ownership: Own data quality for the models you build — writing tests, documentation, and monitoring, and resolving data issues at their root cause across the marketing workflows you support.
4
Code Review & Design: Conduct thorough code reviews, write and share designs publicly before building, and apply simple, reusable modeling patterns that leave the codebase better than you found it.
5
Pipeline Evolution & Observability: Improve existing marketing data pipelines to reduce manual effort and improve performance, enhance observability (logging, metrics, freshness and quality checks), and participate in incident response for the data platform.

Requirements

3–5 years of experience in Analytics Engineering, Data Engineering, or closely related roles, with hands-on ownership of production data models and pipelines.
Strong SQL skills and hands-on experience building well-architected dimensional data models (star schemas, fact/dimension tables, SCDs).
Hands-on experience with the modern data stack, including dbt, Snowflake, and Airflow.
Working knowledge of marketing data and metrics — including paid media performance, attribution concepts, and channel-level measurement — or the ability to ramp quickly.
Demonstrated ability to deliver complete data models and pipelines independently, manage multiple priorities, and write clean, well-documented, well-tested code.
Effective communicator who can collaborate across data, marketing, and engineering teams to understand requirements and deliver solutions.
Experience partnering with Data Scientists on experimentation, attribution, or incrementality measurement.
Familiarity with marketing platforms (ie Google Ads, Meta, Google Analytics, SEO tooling).
Python experience for automation or advanced transformations.
Comfort using AI-assisted developer tools to improve code quality and speed (e.g., generating tests, validating logic, comparing suggestions).
Experience contributing to analytics engineering best practices such as testing, documentation, or data quality standards.