Big Data Engineer for AI Systems and Pipelines

About OpenTrain

OpenTrain AI is the hiring and contracting organization for this remote opportunity. OpenTrain is the #1 platform for finding and building careers in AI training and data labeling, helping contributors discover cutting-edge projects, build their profiles, and apply in minutes.

Creating an OpenTrain account is free. Through this role, your data engineering expertise can contribute directly to the systems and datasets used to train and evaluate advanced AI.

About AI Training and Data Engineering

AI training is the human side of building artificial intelligence. People with technical expertise help prepare, structure, process, and evaluate the data that modern AI systems use to learn, reason, and perform.

Data engineers play an essential role by designing dependable pipelines, transforming large datasets, and maintaining the infrastructure that makes high-quality AI development possible. This is remote work in a fast-growing technology field.

The Role

OpenTrain AI is seeking an intermediate Big Data Engineer to support an initiative focused on training next-generation AI systems. You will use large-scale data engineering expertise to build, refine, and optimize complex datasets and pipelines using real-world inputs.

This is a remote contractor and part-time opportunity. The expected project duration is 1 to 3 months, with a weekly commitment of at least 20 hours.

• Compensation: $30-$80 per hour
• Role type: Contractor and part-time
• Work location: Remote
• Experience level: Intermediate
• Expected commitment: 20+ hours per week
• Project duration: 1 to 3 months

What You'll Do

You will work on scalable data infrastructure and technical workflows that support AI data solutions. The role requires clear documentation, effective communication, and careful attention to data quality, governance, security, and system performance.

• Design, build, and maintain scalable big data pipelines and architectures.
• Collaborate with cross-functional teams to understand technical data requirements and project goals.
• Implement data integration, transformation, and processing workflows with Python and distributed data technologies.
• Manage, tune, and optimize distributed databases and storage systems for performance and efficiency.
• Monitor, troubleshoot, and continuously improve data infrastructure for high availability and accuracy.
• Enforce data quality, governance, and security standards across data assets.
• Document technical solutions clearly and communicate complex concepts in writing and conversation.

Required Qualifications

Applicants should have a proven track record in big data engineering, including hands-on experience building and maintaining large-scale ETL pipelines. You should be comfortable working autonomously in a remote environment and communicating technical concepts clearly in English.

Native or bilingual English proficiency is required. Candidates must be based in one of the approved locations listed below.

• Advanced Python proficiency for data processing, script automation, and pipeline integration.
• Strong experience with big data frameworks such as Hadoop, Apache Spark, or Flink.
• Deep understanding of relational and NoSQL databases, including indexing, query optimization, and schema design.
• Experience with data engineering, ETL pipeline architecture, data modeling, and data warehousing.
• Understanding of distributed storage systems and large-scale data processing.
• Excellent technical writing and verbal communication skills.
• Self-motivated approach and ability to thrive in an autonomous, remote setup.
• Subject-matter expertise in AI systems and big data engineering.
• Comfort working in English with native or bilingual English proficiency.

Preferred Qualifications and Eligible Locations

Experience in fast-paced technology environments or agile global team setups is preferred. Familiarity with MLOps concepts and data science workflows is also a strong plus.

• Hands-on experience with cloud-native big data suites such as AWS, GCP, or Azure.
• Experience in fast-paced tech environments.
• Experience working with agile global teams.
• Familiarity with MLOps concepts.
• Familiarity with data science workflows.
• Eligible locations: United States, United Kingdom, India, Germany, Canada, Ireland, Greenland, Iceland, and Japan.

How to Apply

Create a free OpenTrain account and apply through OpenTrain AI. Highlight your experience with large-scale ETL pipelines, Python, distributed computing, database optimization, and AI data systems so your technical background is easy to evaluate.

• Review the role requirements and confirm your eligible location.
• Prepare examples of relevant data engineering and pipeline work.
• Apply remotely through OpenTrain for consideration.