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# Data Engineer

- **Company:** fairlife, LLC
- **Location:** Chicago, IL, United States
- **Experience:** Expert
- **Salary:** $120,000.0 - $140,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Application Performance Management, Automation of Tests, Microsoft Azure, Software as a Service, Code Review, Information Engineering, Data Warehousing, Dimensional Modeling, Python (Programming Language), Package Management Systems, Azure Active Directory, Kusto Query Language, Search Technologies, SQL Databases, Data Streaming, YAML, Azure Service Bus, Data Server Interface, Azure Data Factory, Apache Spark, Git, Data Lakes, Pyspark, Information Technology, Key Vault, Databricks
- **Published:** September 25, 2026
- **Apply:** https://www.juju.com/job/16_d33f9b372

## About the Role

* Bachelor's degree in computer science, engineering, or related field AND 5+ years of data engineering experience (manufacturing/CPG preferred)
 * Expert-level SQL and strong Python (building shared libraries and frameworks, not just scripts); hands-on Spark/PySpark for large-scale transformation
 * Strong grounding in data warehousing and dimensional modeling (star schemas, Kimball)
 * Proficiency with Azure data services such as SQL databases, Event Hubs, Functions, Data Factory, Key Vault, and Microsoft Entra
 * Experience with Azure DevOps or similar: Git, YAML CI/CD pipelines, artifact/package management, and disciplined code review practices
 * Lakehouse experience (Delta Lake, medallion architecture) in Fabric or Databricks preferred
 * Working knowledge of KQL (Azure Data Explorer, Eventhouse, or Application Insights) a plus
 * Exposure to RAG/semantic search or MCP tool integrations a plus
 * Experience with manufacturing/factory data (MES, historians, IIoT streaming) a plus
 * Excellent communication skills, comfortable engaging non-technical stakeholders
 * Detail-oriented self-starter with a growth mindset and ability to handle ambiguity
 * A natural team player with a habit of helping, documenting, and sharing

## Description

* Design, implement, and operationalize batch and streaming data pipelines that integrate enterprise and factory data sources (ERP, IIoT, SaaS applications, APIs) into our lakehouses
 * Support development and maintenance of dimensional data models (star schemas) in our lakehouses that deliver consistent, well-governed metrics to the business
 * Build reusable frameworks and shared Python libraries (ingestion patterns, incremental loads, telemetry, alerting) that accelerate the whole team, not just one project
 * Own the engineering lifecycle end to end: Git branching, pull requests, CI/CD pipelines in Azure DevOps, automated testing, and environment promotion
 * Monitor, troubleshoot, and optimize solutions for reliability, performance, and cost, building data quality validation and pipeline observability into solutions from the start
 * Embed security and governance into every solution: identity-based authentication, secret management, access control, and responsible handling of sensitive data
 * Contribute to our growing AI-facing platform capabilities, including semantic search indexes, AI-ready data interfaces, and agent tooling
 * Partner with stakeholders across manufacturing and business functions, translating their needs into well-designed solutions and communicating to non-technical audiences
 * Document, share, and support the technical growth of fellow team members


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