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.
Responsibilities
- 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.
Qualifications
- 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.