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# Data Engineer / AI Workflow Engineer

- **Company:** Compunnel Inc.
- **Location:** United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Big Data, Health Informatics, Law Practice Management Software, Cloud Computing, Cloud Database, Information Systems, Data Cleansing, Information Engineering, Extract Transform Load (ETL), Software Debugging, Distributed Computing Environment, Python (Programming Language), Knowledge Management, Unstructured Data, Enterprise Data Management, Data Processing, Enterprise Software Applications, Feature Engineering, Data Ingestion, Large Language Models, Prompt Engineering, Model Validation, Software Troubleshooting, AI Platforms, Information Technology, Data Analytics, Enterprise Integration, Machine Learning Operations, Data Pipelines
- **Published:** June 30, 2026
- **Apply:** https://www.dice.com/job-detail/5fc994fb-36aa-495f-b4ae-a142d0610be9

## About the Role

Job Summary We are seeking an experienced Senior Data Engineer to design, develop, and optimize enterprise data pipelines and AI-enabled data workflows. This role focuses on building scalable ETL solutions, integrating AI capabilities into enterprise platforms, and supporting data-driven analytics across regulated business environments. The ideal candidate will have strong expertise in Python, cloud-based data engineering, ETL development, and AI/ML workflow integration. Key Responsibilities Design, develop, and maintain scalable ETL pipelines for data ingestion, transformation, and delivery across enterprise systems. Develop data engineering solutions supporting analytics, reporting, and AI-driven business use cases. Process and manage structured and unstructured data from multiple enterprise data sources. Collaborate with engineering, product, and data science teams to integrate AI solutions into enterprise platforms. Support AI development workflows including experimentation, model
evaluation, deployment, optimization, and operationalization. Perform data preparation, feature engineering, and validation for AI and machine learning solutions. Ensure data quality, consistency, reliability, performance, and governance across enterprise data pipelines. Automate data processing workflows to improve operational efficiency and scalability. Monitor, troubleshoot, and optimize large-scale data processing pipelines. Develop and maintain technical documentation, data workflows, and implementation standards. Participate in architecture discussions and contribute to enterprise data platform improvements. Support deployment and maintenance of cloud-based analytics and AI solutions. Required Qualifications Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical field, or equivalent professional experience. Minimum 5 years of experience in Data Engineering, ETL Development, or related technical roles. Strong hands-on experience with Python
for ETL development and data processing. Experience designing, developing, and maintaining enterprise data pipelines. Experience working with cloud-based or distributed data processing environments. Experience processing and optimizing large-scale datasets. Familiarity with AI and machine learning development workflows. Experience integrating AI solutions into enterprise applications. Strong troubleshooting, debugging, analytical, and problem-solving skills. Excellent communication and collaboration skills. Preferred Qualifications Experience with enterprise AI tools and workflows, including Large Language Model (LLM) orchestration. Experience with prompt engineering and AI workflow automation. Experience working with AI copilots or enterprise AI platforms. Experience working in regulated enterprise environments. Experience collaborating with product, engineering, and data science teams. Experience supporting enterprise analytics, regulatory reporting, knowledge management, risk management,
healthcare analytics, financial services, Legal Technology, or AI-enabled enterprise data platforms. Education Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical field. Equivalent hands-on experience in data engineering or AI/ML workflows may be considered in lieu of a degree. Education: Bachelors Degree



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