Live opening · Posted 7 days ago

Data Engineer

micro1 · NAMER (Remote)
Linkedin No
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At a glance

The key details from the original listing.

Posted 7 days ago
Companymicro1
LocationNAMER (Remote)
Work modeNo
SourceLinkedin
Listed7 days ago

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About the role

Description supplied by the original job listing.

Job Title: 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.
Key Responsibilities:
Design, develop, and maintain scalable ETL processes to ensure smooth data integration and transformation.
Collaborate closely with cross-functional teams to analyze data needs and implement tailored solutions.
Optimize existing workflows for performance, reliability, and scalability.
Monitor, troubleshoot, and resolve issues in production data pipelines to uphold data integrity.
Write clean, well-documented Python code adhering to industry standards and best practices.
Champion data quality and implement validation mechanisms throughout data processes.
Communicate complex technical concepts to both technical and non-technical stakeholders, prioritizing clear written and verbal interactions.
Required Skills and Qualifications:
Expert-level proficiency in Python programming.
Extensive hands-on experience building and maintaining ETL pipelines and data workflows.
Proven ability to work independently in a fully remote environment.
Exceptional written and verbal communication skills, with a strong focus on clarity and collaboration.
Strong analytical and problem-solving mindset with acute attention to detail.
Demonstrated expertise in debugging and optimizing large-scale data systems.
Solid understanding of data modeling, data warehousing concepts, and best practices in data engineering.
Preferred Qualifications:
Experience within global, distributed teams and working directly with customers.
Exposure to additional programming or scripting languages and modern data stack tools.
Background in supporting highly regulated or data-centric industries.

Work arrangement
No

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