The work
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.
What it pays and takes
The listing does not include a pay rate. This is a part-time contractor role with a weekly commitment of 20 or more hours.
- Open to candidates in India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, Mexico, and Brazil.
- 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.
- Helpful experience includes LLM research or evaluation, developer tools, automation agents, MLOps, data versioning, Great Expectations, Kubernetes, or container security.
How it works
Apply on OpenTrain with your resume, then complete the application on the hiring site.