Data Validation Engineer (Remote)
Hired · United States
- Hybrid
- Contract
- $120,000 / year
- United States
Job highlights
- Design and implement data validation in Docker pipelines.
- Ensure dataset quality, schemas, and model artifacts.
- Collaborate with data engineering, ML, and DevOps.
- Build reliable, reproducible, validated containerized pipelines.
- Work remotely for a technology industry leader.
About the role
Data Validation Engineer (Remote)
We are hiring for one of our clients, seeking a Dockerfile Data Validation Engineer to work on a full-time basis. This individual will be responsible for designing, implementing, and maintaining data-validation workflows inside docker-based build pipelines, ensuring datasets, schemas, and model artifacts meet quality and compliance requirements before deployment. The role involves collaborating with data engineering, machine learning, and devops teams to build reliable, reproducible, and fully validated containerized data pipelines in the technology industry.
Key Responsibilities:
- Develop and optimize dockerfiles with built-in data-validation steps to ensure the quality and compliance of datasets, schemas, and model artifacts.
- Implement label metadata for datasets and implement validation scripts to verify data integrity and consistency.
- Collaborate with data engineering, machine learning, and devops teams to design and implement reliable, reproducible, and fully validated containerized data pipelines.
- Design and implement data-validation workflows to meet specific industry standards and regulations.
- Optimize and maintain existing data-validation processes to ensure scalability and efficiency.
Required Skills & Qualifications:
- Experience in designing, implementing, and maintaining data-validation workflows using Docker and CI/CD pipelines.
- Proficiency in programming languages such as Python and Bash, with experience in scripting and automation.
- Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
- Knowledge of data engineering and machine learning principles, with experience in working with large datasets.
- Strong understanding of industry standards and regulations related to data quality and compliance.
More About the Opportunity:
This role offers a unique opportunity to work with a global leader in the technology industry, driving innovation and excellence in data engineering and validation. As a Dockerfile Data Validation Engineer, you will have the chance to collaborate with a talented team of experts and contribute to the development of cutting-edge data pipelines and workflows.
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.
Key skills/competency
- Data Validation
- Dockerfile
- Docker
- CI/CD
- Python
- Bash
- Data Engineering
- Machine Learning
- DevOps
- Kubernetes
Skills & topics
- Data Validation Engineer
- Data Validation
- Dockerfile
- Docker
- CI/CD
- Python
- Bash
- Data Engineering
- Machine Learning
- DevOps
- Kubernetes
- Remote
- Technology
How to get hired
- Tailor your resume: Highlight experience with Docker, CI/CD, Python, Bash, and data validation workflows.
- Showcase automation skills: Detail projects involving scripting and optimizing containerized data pipelines.
- Emphasize collaboration: Mention experience working with data engineering, ML, and DevOps teams.
- Demonstrate compliance knowledge: Clearly state understanding of data quality and industry regulations.
- Apply directly: Submit your application through the Hired platform, focusing on technical ability.
Technical preparation
Behavioral questions
Frequently asked questions
- What is the work arrangement for the Data Validation Engineer role at Hired?
- The Data Validation Engineer position at Hired is a fully remote role, allowing you to work from anywhere. This provides flexibility and the opportunity to join a global leader in the technology industry without geographical constraints.
- What programming languages are essential for the Data Validation Engineer position?
- Proficiency in Python and Bash is essential for this Data Validation Engineer role. These languages are crucial for scripting, automation, and developing data-validation workflows within Docker-based pipelines.
- How does Hired ensure fair hiring practices for the Data Validation Engineer role?
- Hired operates on an Equal Opportunity Employer basis, hiring solely based on skills and expertise. All qualified candidates are welcome, and applications are reviewed based on demonstrated technical ability and qualifications, not background or history.
- What is the primary focus of the Data Validation Engineer role at Hired?
- The primary focus is on designing, implementing, and maintaining data-validation workflows within Docker-based build pipelines. This ensures the quality and compliance of datasets, schemas, and model artifacts before deployment.
- What kind of collaboration is expected for this Data Validation Engineer job?
- This role requires close collaboration with data engineering, machine learning, and DevOps teams. The goal is to collectively build reliable, reproducible, and fully validated containerized data pipelines.