Big Data Engineer - Remote

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.

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.

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.

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.