Design, develop, and maintain scalable data pipelines and ETL/ELT processes supporting AI research, prototyping, and production use cases.
Collaborate with AI scientists and engineers to translate data requirements into ingestion, transformation, and serving solutions.
Apply data governance and security controls ensuring compliance, auditability, and protection of sensitive information.
Monitor, troubleshoot, and resolve data pipeline failures, performance issues, and schema changes.
Continuously improve reliability through testing, observability, documentation, and automation.
Design and maintain efficient data models supporting analytics, ML workflows, and AI agent operations.

Typically 3+ years of professional experience in data engineering, including production-grade pipeline development.
Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
Strong proficiency in Python; working experience with Java or Scala.
Solid knowledge of SQL and experience with NoSQL databases.
Familiarity with data warehousing and lakehouse platforms.
Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP).
Experience with orchestration frameworks and CI/CD practices for data pipelines.

AI Data Engineer

Key skills