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. Main tasks listed: 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.
Experience
See the official listing for the full requirements.
Selection process
Apply through the official Turing page (free account required). The listing describes this selection process: Interviews (30-60 min technical discussion in QODE).
Eligibility
India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, Mexico, Brazil (as stated on the listing)