Azure Stack Data Engineer

About the Role

Key responsibilities include designing data pipelines with Azure Data Factory, Azure Synapse, and Azure Functions, and developing ETL processes for both structured and unstructured data. The engineer will optimize storage in Azure Data Lake and Azure SQL, integrate data from ERP, CRM, and legacy platforms, and automate workflows using Azure Logic Apps and Event Hub. They will also ensure data quality, security, and compliance, implement monitoring and alerting, and collaborate with analysts, architects, and stakeholders to provide BI‑ready datasets. • Design and implement Azure‑based data pipelines using Data Factory, Synapse, and Functions. • Develop ETL processes for structured and unstructured data. • Optimize storage solutions in Azure Data Lake and Azure SQL. • Integrate data from ERP, CRM, and legacy systems; automate workflows with Logic Apps and Event Hub. • Ensure data quality, security, compliance, and set up monitoring and alerting. • Collaborate with analysts, architects, and business stakeholders to deliver BI‑ready datasets. • Apply Python, SQL, and scripting expertise for automation tasks. • Follow DevOps and CI/CD practices for data solution deployment. • Stay current with AI, IoT, and advanced analytics trends to drive innovation.

Key Responsibilities

• ▸data pipelines
• ▸etl development
• ▸storage optimization
• ▸data integration
• ▸data governance
• ▸ci/cd

What You Bring

AAON is seeking an experienced Azure Stack Data Engineer to design, build, and optimize data solutions using Microsoft Azure technologies. The role focuses on creating secure, scalable, and efficient data pipelines and storage that support advanced analytics and business intelligence. The ideal candidate combines strong technical expertise with business acumen and collaboration skills to deliver data‑driven insights across the enterprise. Required competencies cover deep knowledge of Azure services such as Data Factory, Synapse Analytics, Data Lake, Azure SQL, and hybrid Azure Stack environments, as well as strong ETL, data modeling, Python, SQL, and scripting skills. The candidate must understand how data solutions impact business processes, communicate technical concepts clearly, work effectively in cross‑functional teams, and stay adaptable to emerging technologies. Innovation is valued, with an expectation to identify automation opportunities and keep up with AI, IoT, and advanced analytics trends. Qualifications include a Bachelor’s degree in Computer Science, Information Systems, or a related field and at least three years of data engineering experience with Azure technologies. Familiarity with DevOps practices, CI/CD pipelines, Power BI, and Fabric is required; preferred experience includes Azure Stack Hub, hybrid cloud environments, and containerization using Docker or Kubernetes. The work environment is a climate‑controlled office with prolonged sitting and monitor use, and the company provides accommodations for disabilities as needed. • Leverage knowledge of Azure Stack, hybrid cloud, and containerization (Docker/Kubernetes).

Requirements

• ▸azure stack
• ▸docker
• ▸kubernetes
• ▸data factory
• ▸python
• ▸bachelor’s

Work Environment

Hybrid