What the work is
Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input.
Key Responsibilities
- Design, build, and maintain scalable big data pipelines and architectures to support robust data solutions.
- Collaborate with cross-functional teams to understand and deliver on data requirements and business objectives.
- Implement data integration, transformation, and processing solutions using Python and relevant big data technologies.
- Develop, manage, and optimize distributed databases and storage systems for efficiency and reliability.
- Monitor, troubleshoot, and enhance data systems to ensure high availability and performance.
- Enforce data quality, security, and governance standards across all solutions.
- Document solutions and communicate complex technical concepts effectively, both in writing and verbally.
Who gets hired
- Proven expertise in big data engineering with hands-on experience building and maintaining large-scale data pipelines.
- Advanced proficiency in Python for data processing, automation, and integration.
- Deep understanding of relational and NoSQL databases, including optimization and management techniques.
- Experience with distributed data processing frameworks (e.g., Hadoop, Spark, Flink).
- Strong foundation in data modeling, ETL processes, and data warehousing principles.
- Excellent written and verbal communication skills, with the ability to convey technical ideas clearly to both technical and non-technical stakeholders.
- Detail-oriented, proactive, and self-motivated, thriving in remote and autonomous work environments.
Preferred Qualifications
- Prior experience in fast-paced or startup-like environments supporting global teams.
- Expertise with cloud-based big data platforms (e.g., AWS, GCP, Azure).
- Familiarity with machine learning operations and data science workflows is a plus.
Pay
$30–80/hr, fully remote. How payouts and tax work.