🐳 Dockerfile Data Validation Engineer – Remote AI Opportunity

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🐳 Dockerfile Data Validation Engineer – Remote AI Opportunity | Turing Are you an experienced DevOps Engineer with strong knowledge of Docker, Python, Bash, and CI/CD? Turing is looking for engineers to build and maintain reliable data-validation workflows inside Docker-based pipelines. This opportunity is ideal for DevOps and infrastructure professionals who have experience with containerization, automation, data validation, and CI/CD workflows and want to contribute to advanced AI projects. 💼 Job Details Position: Dockerfile Data Validation Engineer Company: Turing Job Category: Cloud & Infrastructure Job Type: Remote Contractor Location: 🇮🇳 India, 🇵🇰 Pakistan, 🇳🇬 Nigeria, 🇰🇪 Kenya, 🇪🇬 Egypt, 🇬🇭 Ghana, 🇧🇩 Bangladesh, 🇹🇷 Turkey, 🇲🇽 Mexico, 🇧🇷 Brazil Contract Duration: 2–4 weeks Expected Start: Next week Commitment: 20, 30, or 40 hours/week Daily Requirement: At least 4 hours/day PST Overlap: 4 hours required 🔧 Required Skills Python Bash Docker & Dockerfiles CI/CD Data validation Data schemas and formats Container registries DevOps workflows 📋 What Will You Do? In this role, you will be responsible for designing and maintaining data-validation workflows within Docker-based build pipelines. Your responsibilities include: Developing and optimizing Dockerfiles with built-in data-validation steps. Creating Dockerfile LABEL metadata for dataset versions, schemas, and lineage. Writing Python/Bash scripts to validate data schemas, integrity, and quality. Integrating validation checks into CI/CD pipelines. Implementing fail-on-bad-data checks before deployment. Documenting Dockerfile labeling, validation standards, and data governance practices. Working with data engineering, machine learning, and DevOps teams to create reliable and reproducible containerized pipelines. 🎓 Requirements Turing is looking for experienced DevOps Engineers with 4+ years of experience. You should have: Strong experience with Docker and Dockerfiles. Proficiency in Python or Bash. Knowledge of data formats, schemas, and validation tools. Familiarity with CI/CD systems. Experience working with container registries. ⭐ Nice to Have Experience with any of the following can be an advantage: LLM research or AI evaluation projects Developer tools or automation agents MLOps workflows Data versioning Great Expectations Kubernetes Container security tools 🤖 Why Consider This Opportunity? This is a chance to work remotely on cutting-edge AI and data infrastructure projects while helping build reliable, reproducible, and validated containerized pipelines. 💰 Referral Bonus: $150 🧪 Evaluation Process The evaluation process takes approximately 75 minutes and includes: 30–60 minute technical discussion in QODE ⏰ Work Commitment You can choose from: 20 hours/week 30 hours/week 40 hours/week A 4-hour overlap with PST is required. ⚠️ Important: This is a short-term contractor assignment with a 2–4 week duration and no medical or paid leave. Apply Now