Enterprise Systems Engineer

We are seeking an experienced Enterprise Systems Engineer with a focus on Data & AI to maintain and enhance complex data flows within our enterprise environment. This hybrid Data Engineer role specializes in designing and implementing ETL pipelines between on-premises systems and cloud platforms, such as Microsoft Fabric, to deliver real-time reporting, analytics, and actionable data insights powered by AI and automation. The ideal candidate excels at utilizing low-code/no-code tools to efficiently achieve organizational objectives.

• High proficiency with low-code/no-code tools for building data-driven objectives.
• Advanced experience with Microsoft Fabric and modern ETL tools.
• Strong familiarity with AI tools and their applications in data engineering and automation.
• Experience supporting researcher-specific pipelines is a plus.
• Proven ability with data management tools and validation of data movement.
• Ability to query databases using SQL, CLI, and API commands.
• Working knowledge of scripting and data formats such as PowerShell, Python, and JSON.
• Experience integrating SaaS applications with on-premise systems.
• Project leadership experience.

Education:

• Bachelor's degree in Computer Science, Information Systems, Business Administration, or a related field required. (Four years of experience may be substituted for a degree.)

Experience:

• Minimum of three (3) years of IT-related experience with data management tools, ETL processes, or cloud data integration required.
• Demonstrated experience in testing and validation of data movement across various repositories.

This position may require the ability to maintain the security and integrity of UT San Antonio and its infrastructure per Texas EO-GA-48.

• Analyze current IT operational processes and business requirements to identify new data and technology specifications.
• Design and implement complex ETL pipelines and data movement solutions between on-premise systems and cloud data platforms.
• Utilize low-code/no-code tools to automate data objectives and business processes.
• Leverage AI and automation to enhance data insights, real-time reporting, and system efficiency.
• Prepare flow charts and models based on system specifications to support configuration design.
• Monitor data system performance and recommend/implement improvements or modifications.
• Test data solutions to validate functionality, usability, and data integrity.
• Serve as a technical expert for systems integration, addressing compatibility across multiple platforms and SaaS integrations.
• Collaborate with IT teams and business units to ensure process improvements align with business requirements.
• Maintain technical documentation for system users and support ongoing operations and development.
• Work with researchers and institutional team members to articulate and access data requirements for specialized research pipelines.
• Perform other duties as assigned.