Dockerfile Data Validation Engineer

Explore this software engineering opportunity. The information below summarizes the supplied role details; check the application page for the latest requirements and availability.

Role highlights & qualifications

• PythonBashDockerCI/CD
• About the Role: We are seeking an engineer responsible for designing, implementing, and maintaining data-validation workflows inside Docker-based build pipelines. This role involves creating and managing Dockerfile labels, metadata standards, and validation scripts that ensure datasets, schemas, and model artifacts meet quality and compliance requirements before deployment.
• The work involves work closely with data engineering, machine learning, and DevOps teams to build reliable, reproducible, and fully validated containerized data pipelines.
• Develop and optimize Dockerfiles with built-in data-validation steps.
• Implement LABEL metadata for dataset versions, schemas, and lineage.
• Create validation scripts (Python/Bash) for schema checks, data integrity, and quality control.
• Integrate validation steps into CI/CD pipelines and enforce fail-on-bad-data checks.
• Document standards for Dockerfile labeling, validation logic, and data governance.
• Experienced DevOps engineers with 4+ years of experience
• Experience in Docker & Dockerfiles.

Information is summarized from the supplied job posting. Please verify location eligibility, compensation, contractual terms and current availability on the application page.