> Markdown version of [/jobs/ext/622821-analytics-engineer](https://www.wearedevelopers.com/jobs/ext/622821-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:** fairlife, LLC - **Location:** Chicago, IL, United States - **Experience:** Expert - **Salary:** $95,000.0 - $105,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Business Analytics Applications, Automation of Tests, Continuous Integration, DevOps, Performance Tuning, Power BI, Azure DevOps Pipelines, SQL Databases, Transact-SQL, Apache Spark, Git, Microsoft Fabric, Star Schema - **Published:** June 24, 2026 - **Apply:** https://www.dice.com/job-detail/6ca1614f-29a8-4e0a-b455-3403c2cbaf81 ## About the Role * 4+ years delivering analytics engineering or equivalent experience building production-grade data products (pipelines + semantic models + governed metrics). * Expert SQL (T-SQL + SparkSQL) and strong semantic modeling skills (Power BI / Tabular), including performance tuning, star schema, and metric governance. * Proven ability to build stakeholder trust and drive adoption through clear communication, documentation, and enablement (not just delivery). * Prior engagement delivering AI-enabled analytics solutions (agents/copilots/workflow automation) with evaluation/monitoring and safe deployment patterns (human-in-the-loop, auditability). * Demonstrated experience with CI/CD and DevOps for analytics (Git, Azure DevOps pipelines, automated testing, release processes) orchestration, automation, testing, or ML/AI evaluation harnesses. * Ability to build training + enablement programs and measure adoption/value. * Demonstrated ability to use modern development accelerators (e.g., coding assistants/agents) responsibly to increase throughput while maintaining quality and governance. * Bachelors in a technical field, masters preferred. ## Description * Build and own production-grade, domain-oriented data products in Microsoft Fabric (Lakehouse/Delta) with documented logic, monitoring, and clear SLAs/ownership. * Develop governed semantic models and a scalable KPI/metric system that enables consistent, trusted self-serve decision intelligence across Finance, HR, Demand, and Site Operations. * Implement CI/CD, automated testing, and performance optimization for pipelines, models, and DAX/SQL to ensure reliability and speed at scale. * Deliver decision-ready insights ("so what / now what") through dashboards, alerts, and embedded workflows that accelerate decision velocity and improve operational outcomes. * Support design and development of agentic AI solutions that automate multi-step decision workflows with governed data, guardrails, auditability, human-in-the-loop controls, and evaluation metrics. * Lead AI and decision intelligence enablement: training, playbooks, office hours, and adoption programs; continuously measure engagement, value realization, and iterate based on feedback. * Serve as a DI force multiplier by coaching teammates on analytics engineering, semantic modeling, and AI delivery best practices; create reusable templates and standards ("build once, use often") * Partner cross-functionally to align on priorities, definitions, and tradeoffs; operate with strong ownership, speed, and accountability, As our recruitment is primarily handled in-house, we work only occasionally with external agencies, and only those on our existing, pre-approved vendor list. 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