[Remote] Data Engineering & AI Workflow Specialist
Note: The job is a remote job and is open to candidates in USA. Dice is a company seeking a Data Engineering & AI Workflow Specialist. The role involves designing and maintaining ETL data pipelines, collaborating with teams to integrate AI solutions, and ensuring data quality for AI/ML models.
Responsibilities
- Design, build, and maintain scalable ETL data pipelines to ingest, transform, and deliver data across systems
- Work with structured and unstructured data sources to support downstream analytics and AI use cases
- Collaborate with engineering and product teams to integrate AI-driven solutions into existing platforms
- Develop and refine AI development workflows, including experimentation, evaluation, and deployment support
- Support data preparation, feature engineering, and validation for AI/ML models
- Ensure data quality, consistency, and performance across pipelines
- Assist in automating processes and improving operational efficiency
- Document technical designs, workflows, and implementation details for maintainability and handoff
Skills
- Strong experience with ETL/data processing (Python)
- Experience building and maintaining data pipelines in cloud or distributed environments
- Familiarity with AI/ML development workflows
- Ability to work with large datasets and optimize performance
- Strong problem-solving and debugging skills
- Bachelors degree in Computer Science, Information Systems, Engineering, or a related technical field
- Equivalent practical experience in data engineering or AI/ML workflows may be considered in lieu of a degree
- 5+ years of experience in data engineering, ETL development, or related technical roles
- 1+ years of experience working with or supporting AI/ML development workflows (e.g., data preparation, model lifecycle, or AI integration into applications)
- Exposure to enterprise AI tooling (e.g., Copilot, LLM orchestration, prompt workflows, or similar)
- Experience working in regulated or enterprise data environments
- Prior experience supporting cross-functional teams (product, engineering, data science)
Company Overview
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