Remote Position
[Remote] Remote | Big Data Engineer — $30–$80/hour
🌍 Remote · United States
💼 Full-time
Note: The job is a remote job and is open to candidates in USA. 24-MAG LLC offers a part-time consulting opportunity for an experienced Big Data Engineer supporting an advanced AI development project. The role focuses on designing and maintaining scalable data pipelines and distributed systems, developing Python-based processing and integration workflows, and optimizing databases and storage.
Responsibilities
- Design, build, and maintain scalable data pipelines and big-data architectures
- Develop reliable workflows for ingesting, transforming, processing, and delivering large volumes of data
- Translate technical and business requirements into robust data-engineering solutions
- Apply appropriate architectural patterns for distributed and high-volume data systems
- Ensure data workflows remain scalable, maintainable, and suitable for production-oriented environments
- Develop data-processing, automation, and integration solutions using Python
- Implement ETL and data-transformation workflows across structured and unstructured data sources
- Work with distributed processing technologies and modern big-data frameworks
- Build reproducible and efficient programmatic workflows for large-scale data operations
- Identify opportunities to improve processing efficiency, reliability, and maintainability
- Develop, manage, and optimise relational, NoSQL, distributed database, and storage systems
- Apply data-modelling and data-warehousing principles to support scalable analytical and operational workloads
- Monitor data-system performance and identify bottlenecks, failures, and reliability issues
- Troubleshoot performance, availability, and integration problems across distributed data environments
- Optimise storage, queries, and processing workflows for efficiency and resilience
- Apply appropriate data-quality, security, and governance standards across engineering workflows
- Collaborate with technical and cross-functional stakeholders to understand data requirements and delivery priorities
- Document architectures, data flows, implementation decisions, and technical trade-offs
- Communicate complex engineering concepts clearly to both technical and non-technical audiences
- Support consistent engineering standards across remote and distributed project environments
Skills
- Proven professional experience in big-data engineering with hands-on responsibility for large-scale data pipelines and architectures
- Advanced proficiency in Python for data processing, automation, integration, and related engineering workflows
- Deep understanding of relational and NoSQL databases, including optimisation, management, and performance considerations
- Practical experience with distributed data-processing frameworks such as Hadoop, Spark, Flink, or comparable technologies
- Strong foundation in data modelling, ETL processes, data integration, and data-warehousing principles
- Ability to troubleshoot distributed systems, database performance, pipeline failures, and data-quality issues
- Excellent written and verbal communication skills
- Ability to explain technical concepts clearly to both engineering and non-technical stakeholders
- Strong attention to detail, initiative, and ability to work independently in remote environments
- Experience supporting fast-paced, startup-like, or globally distributed teams is advantageous
- Familiarity with cloud-based data platforms such as AWS, GCP, or Azure is advantageous
- Exposure to machine-learning operations, data-science workflows, or adjacent AI infrastructure is beneficial
Benefits
- Fully remote
Company Overview