Big Data Engineer

Role Overview

Apply big data engineering expertise to help train next-generation AI systems through high-quality, real-world data input that improves how models learn, reason, and perform.

Key Responsibilities

• Design, build, and maintain scalable big data pipelines and architectures.
• Partner with cross-functional teams to deliver data solutions aligned with requirements and business objectives.
• Implement data integration, transformation, and processing solutions using Python and big data technologies.
• Develop, manage, and optimize distributed databases and storage systems for reliability and efficiency.
• Monitor, troubleshoot, and improve data systems to maintain availability and performance.
• Apply data quality, security, and governance standards across solutions.
• Document technical solutions and clearly communicate complex concepts in writing and conversation.

Qualifications

• Demonstrated big data engineering experience building and maintaining large-scale data pipelines.
• Advanced Python skills for data processing, automation, and integration.
• Deep knowledge of relational and NoSQL databases, including optimization and management.
• Experience with distributed processing frameworks such as Hadoop, Spark, or Flink.
• Strong knowledge of data modeling, ETL processes, and data warehousing.
• Clear written and verbal communication skills for technical and non-technical audiences.
• Detail-oriented, proactive, self-motivated, and effective in an autonomous remote environment.
• Preferred: experience supporting global teams in fast-paced or startup-like settings, cloud big data platforms such as AWS, GCP, or Azure, and familiarity with MLOps or data science workflows.

Work Terms

• Remote independent contractor engagement.

Compensation

• $30 to $80 per hour.

Application Process

• Apply using an email address or Google account. Continuing the application confirms agreement to the applicable terms and privacy policies; FAQs are available for questions.