AI Summary
Design, develop, and optimize large-scale data pipelines using Hadoop, Spark, and related big data technologies. Collaborate closely with data scientists and machine learning engineers to enable AI and LLM initiatives. Enforce best practices across data engineering, including performance optimization, security, and scalability.
Key Highlights
Design and optimize large-scale data pipelines
Collaborate with data scientists and machine learning engineers
Enforce best practices across data engineering
Key Responsibilities
Design, develop, and optimize large-scale data pipelines
Build and maintain scalable data architectures
Integrate and manage real-time data streams
Deploy, orchestrate, and monitor distributed data processing systems
Collaborate closely with data scientists and machine learning engineers
Document complex data workflows and create clear training materials
Enforce best practices across data engineering
Technical Skills Required
Benefits & Perks
Hourly contract
Remote work
Job Description
Position: Data Engineer – AI Trainer
Type: Hourly contract
Compensation: $30-$60/hr
Location: Remote
Commitment: 10 to 40 hours per week
Role Responsibilities
- Design, develop, and optimize large scale data pipelines using Hadoop, Spark, and related big data technologies.
- Build and maintain scalable data architectures that support AI model training and analytics workloads.
- Integrate and manage real time data streams using Kafka, ensuring data reliability and quality.
- Deploy, orchestrate, and monitor distributed data processing systems on cloud platforms.
- Collaborate closely with data scientists and machine learning engineers to enable AI and LLM initiatives.
- Document complex data workflows and create clear training materials for technical teams.
- Enforce best practices across data engineering, including performance optimization, security, and scalability.
- Support AI and generative AI use cases through high quality data curation and pipeline design.
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- BSc in Computer Science, Data Engineering, or a closely related field.
- Strong hands on experience with big data technologies including Hadoop and Spark.
- Proven expertise using Kafka for real time data streaming and integration.
- Solid background in data engineering with experience building and scaling ETL pipelines.
- Practical experience working with major cloud platforms such as AWS, GCP, or Azure.
- Proficiency in programming or scripting languages such as Python, Scala, or Java.
- Excellent written and verbal communication skills with the ability to explain complex technical concepts.
- Strong problem solving and troubleshooting skills in distributed systems.
- Ability to work independently in a fully remote, collaborative environment.
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