Dockerfile Data Validation Engineer

You will build and maintain validation workflows inside Docker-based build pipelines. Your work will help check datasets, schemas, and model artifacts before deployment so containerized data pipelines remain reliable and reproducible.

• Develop and improve Dockerfiles with built-in data-validation steps.
• Add Docker LABEL metadata for dataset versions, schemas, and data lineage.
• Create Python or Bash scripts for schema checks, data integrity checks, and quality control.
• Connect validation steps to CI/CD pipelines and enforce fail-on-bad-data checks.
• Document Dockerfile labeling, validation logic, and data-governance standards.
• Work across data engineering, machine learning, and DevOps workflows.

The listing does not include a pay rate. This is a part-time contractor role with a weekly commitment of 20 or more hours.

• Fluent in English.
• At least four years of DevOps experience.
• Strong experience with Docker and Dockerfiles.
• Proficiency in Python or Bash for validation scripting.
• Knowledge of data formats, schemas, and validation tools.
• Familiarity with CI/CD systems and container registries.