Note: The job is a remote job and is open to candidates in USA. Dice is seeking a Data Engineer / AI Workflow Engineer to support the development and enhancement of enterprise data processing pipelines and AI-driven workflows. This role will focus on designing, building, and optimizing ETL processes while contributing to the integration and operationalization of AI solutions within a business environment.

Responsibilities

• Design, develop, and maintain scalable ETL data pipelines for data ingestion, transformation, and delivery across systems
• Work with both structured and unstructured data sources to support analytics and AI-driven use cases
• Collaborate with engineering, product, and data teams to integrate AI solutions into existing platforms
• Support AI development workflows including experimentation, evaluation, deployment, and optimization
• Perform data preparation, feature engineering, and validation activities for AI/ML models
• Ensure data quality, reliability, consistency, and performance across pipelines
• Automate data processes and improve operational efficiency
• Troubleshoot data pipeline issues and optimize performance for large-scale datasets
• Create and maintain technical documentation, workflows, and implementation details

Skills

• 5+ years of experience in Data Engineering, ETL Development, or related technical roles
• Strong hands-on experience with Python for ETL and data processing
• Experience designing and maintaining data pipelines in cloud or distributed environments
• Experience working with large datasets and improving data processing performance
• Familiarity with AI/ML development workflows and AI solution integration
• Strong troubleshooting, debugging, and problem-solving skills
• Bachelor's degree in Computer Science, Information Systems, Engineering, or related technical field
• Equivalent hands-on experience in data engineering or AI/ML workflows may be considered in place of a degree
• 5+ years of data engineering, ETL, or related experience
• 1+ years supporting AI/ML development workflows, including data preparation, model lifecycle support, or AI integration into applications
• Experience with enterprise AI tools and workflows such as: LLM orchestration, Prompt engineering/workflows, AI copilots or similar AI platforms
• Experience working in enterprise or regulated data environments
• Experience collaborating with cross-functional teams including: Product teams, Engineering teams, Data Science teams

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