Analytics Engineer II
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Job Description
Analytics Engineer II building trusted marketing data models and pipelines for Instacart’s grocery delivery platform. Supporting attribution, paid marketing, SEO, and retailer marketing analytics.
Responsibilities:
- Build and maintain dimensional data models and ETL pipelines supporting Paid Marketing, SEO, Retailer Marketing, and attribution
- Deliver complete data assets end-to-end with minimal oversight
- Collaborate with Data Scientists, Analysts, and Marketing stakeholders to translate analytical needs into data requirements
- Deliver trusted, decision-ready datasets
- Own data quality through tests, documentation, monitoring, and root-cause resolution of data issues
- Conduct code reviews and share designs before implementation
- Apply simple, reusable modeling patterns
- Improve marketing data pipelines to reduce manual effort and improve performance
- Enhance observability through logging, metrics, freshness checks, and quality checks
- Participate in data platform incident response
Requirements:
- 3–5 years of experience in Analytics Engineering, Data Engineering, or closely related roles
- Hands-on ownership of production data models and pipelines
- Strong SQL skills
- Experience building dimensional data models, including star schemas, fact/dimension tables, and SCDs
- Experience with dbt, Snowflake, and Airflow
- Working knowledge of marketing data and metrics, including paid media performance, attribution concepts, and channel-level measurement, or ability to ramp quickly
- Ability to deliver complete data models and pipelines independently
- Ability to manage multiple priorities
- Ability to write clean, well-documented, well-tested code
- Effective communication and cross-functional collaboration skills
- Experience partnering with Data Scientists on experimentation, attribution, or incrementality measurement preferred
- Familiarity with Google Ads, Meta, Google Analytics, and SEO tooling preferred
- Python experience preferred
- Comfort using AI-assisted developer tools preferred
- Experience contributing to analytics engineering best practices preferred
Benefits:
- New hire equity grant
- Annual refresh grants
- Flexible choice of work location (home, office, or coffee shop)
- Regular in-person events
- Market-competitive compensation and benefits
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