The opportunity
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.
What you'll do
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.
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.
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.
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.
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.
–5 years of experience in Analytics Engineering, Data Engineering, or closely: related roles, with hands-on ownership of production data models and pipelines.
What they're looking for
- 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.
