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.

Although this role will primarily be Remote, applicants local to the San Antonio area are strongly preferred as some on-site visits may be required as needed.

• 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 is highly preferred.

• 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.