Required Skills
big data
Python
databases
data engineering
About micro1
micro1 is the leading AI data lab for training frontier models and evaluating AI agents. Experts contribute their diverse subject matter knowledge across domains such as finance, healthcare, STEM engineering, and more. micro1 transforms that real-world expertise into high-quality training data, evaluations, and feedback loops that improve how AI systems learn, reason, and perform.
Our platform identifies and vets top talent through an AI recruiter, enabling high-quality expert contributions at scale. We aim to enable 1 billion people to do meaningful work by applying their expertise to AI. As our global expert network grows, micro1 is building the human intelligence layer for frontier AI.
Job Title: Big Data Engineer
Job Type: Contractor
Location: Remote
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.
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.
Required Skills and Qualifications:
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.
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.
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