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Quik Hire Staffing · India

Data Engineer (Data Validation) (Remote)

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- Role: Data Engineer (Data Validation) (Remote)

- Location: Remote (Work from Anywhere)

Role Overview:

We are hiring for one of our clients, seeking a Dockerfile Data Validation Engineer to work on a full-time basis. The engineer will design, implement, and maintain data‑validation workflows inside Docker‑based build pipelines. The position supports cutting‑edge AI projects that require reliable, reproducible, and fully validated containerized data pipelines.

Key Responsibilities:

• Develop and optimize Dockerfiles that embed data‑validation steps for datasets, schemas, and model artifacts.

• Implement label metadata standards to track dataset versions, schema definitions, and data lineage within container images.

• Create validation scripts in Python or Bash to perform schema checks, data integrity verification, and quality‑control assessments.

• Integrate validation steps into CI/CD pipelines, enforcing fail‑on‑bad‑data policies to prevent non‑compliant releases.

• Document labeling conventions, validation logic, and data‑governance procedures for cross‑functional teams.

Required Skills & Qualifications:

• Minimum four years of professional experience as a DevOps engineer with strong expertise in Docker and Dockerfile authoring.

• Proficiency in Python or Bash for building automated validation scripts and command‑line tools.

• Working knowledge of data formats, schema definition languages, and validation utilities commonly used in AI pipelines.

• Experience with CI/CD systems and container registries to automate build, test, and deployment workflows.

• Familiarity with data‑versioning concepts, MLOps practices, or tools such as Great Expectations is preferred.

More About the Opportunity:

This role offers a unique opportunity to work with a global leader in the technology, information and internet sector, contributing to the delivery of reliable AI systems for enterprise customers. The engineer will collaborate with data engineering, machine learning, and DevOps teams to ensure that data assets meet quality and compliance standards before they reach production.

Equal Opportunity Employer:

We hire based on skills and expertise. All qualified candidates are welcome regardless of background, experience, or prior employment history. Applications are reviewed solely on demonstrated technical ability and qualifications.

Apply Now!

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