> Markdown version of [/jobs/ext/1884794-analytics-engineer](https://www.wearedevelopers.com/jobs/ext/1884794-analytics-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Analytics Engineer - **Company:** Stott and May - **Location:** Chicago, IL, United States (Remote available) - **Experience:** Expert - **Salary:** $140,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Business Analytics Applications, Data Analysis, Information Engineering, Data Mart, Python (Programming Language), Operational Databases, SQL Databases, Sql Optimization, Snowflake, Data Management - **Published:** August 1, 2026 - **Apply:** https://find.stottandmay.com/job/senior-analytics-engineer-78492/apply ## About the Role * 5+ years in Analytics Engineering or Data Engineering * 3+ years of production dbt experience * Strong Snowflake, SQL, and Python skills * Experience owning analytics solutions end-to-end * Excellent stakeholder communication skills ## Description This is a hands-on senior IC role where you'll build and own production data assets using Snowflake, dbt, SQL, and Python, while partnering with Finance, Supply Chain, Pricing, and Operations to deliver scalable analytics solutions. You'll: * Build and own production dbt models and Snowflake data marts * Write advanced SQL and Python for automation, testing, and data quality * Modernize legacy reporting into a cloud-native analytics platform * Partner directly with business stakeholders to solve complex data challenges * Mentor engineers and help define analytics engineering best practices (no direct reports) ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Data Science on Software Data](https://www.wearedevelopers.com/videos/162-data-science-on-software-data) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [The Innovation Formula: Fast Prototyping, Data Analysis, and Real User Insights](https://www.wearedevelopers.com/videos/1421-the-innovation-formula-fast-prototyping-data-analysis-and-real-user-insights) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)