Sr. Data Engineer - AI
Dairy Farmers of America
Kansas City, KS · Posted November 1, 2026
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November 2026
Rankings about data & analytics jobs
- Best cities for data and analytics jobs #1 New York (1,713 openings)
- Best cities for data and analytics pay after cost of living #1 Foster ($232k)
- Most requested AI skills in data and analytics jobs #1 Machine learning engineering (17.1%)
- AI tools named most often in data and analytics jobs #1 Databricks (7.6%)
- Employers with the most data and analytics jobs #1 Amazon (711 roles)
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How AI is used in this kind of work
Among database architects, AI is already used for a large share of the tasks. Measured exposure for database architects: 58% (high).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
Skills this job asks for
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About the job
Serve in a senior-level technical role designing, building, and supporting secure, scalable data pipelines that connect enterprise data sources to AI/ML models. Ensure data is accurate, current, compliant, and aligned with enterprise AI governance standards while independently solving complex integration challenges and advancing data engineering best practices. Provide practical front-end development support using TypeScript, JavaScript, Vue, and Quasar to help deliver intuitive AI-enabled applications.
Job Duties and Responsibilities:
Design, build, and optimize scalable ETL/ELT pipelines that ingest, transform, and integrate structured and unstructured enterprise data for AI/ML model training and inference
Ensure data is accurate, current, reliable, and secure through cleansing, normalization, validation, automation, continuous updates, monitoring, and error handling
Troubleshoot complex integration and performance issues, remove bottlenecks, and apply appropriate techniques such as caching, distributed processing, and specialized ETL patterns
Own key AI data infrastructure components and ensure they are scalable, maintainable, and supported by effective monitoring, logging, documentation, data lineage, and quality metrics
Apply enterprise architecture, AI governance, privacy, security, coding, and CI/CD standards to data solutions and communicate risks or limitations to leadership
Partner with Software engineers, data architects, domain experts, product teams, and platform teams to align data solutions with model requirements, business goals, and enterprise standards
Develop and support front-end components for AI-enabled applications using TypeScript, JavaScript, Vue, and Quasar to deliver intuitive, maintainable user experiences
Independently deliver assigned work, influence cross-team decisions, promote data engineering best practices, and evaluate technologies that improve AI data delivery
The requirements herein describe the general nature and level of work performed by the employee but are not a complete list of responsibilities, duties, and skills required. Other duties may be assigned as needed