CONTRACTORRemoteActive
Big Data Engineer
micro1 is engaging Big Data Engineers to apply their expertise in large-scale data engineering, distributed systems, databases, and Python to help train next-generation AI systems. Contributors will design and maintain scalable data pipelines and architectures, implement data integration and transformation workflows, optimize distributed databases and storage systems, and ensure data quality, security, governance, availability, and performance. The role combines hands-on big data engineering with cross-functional collaboration and clear technical communication.
Salary
USD30 - USD80 / hour
Department
Data Engineering & Big Data
Experience
Proven hands-on experience in big data engineering, including building and maintaining large-scale data pipelines, with advanced Python proficiency and strong knowledge of distributed processing frameworks, relational and NoSQL databases, ETL, data modeling, and data warehousing
Curated by Farooq77 Jobs
Role fit snapshot
- Engagement
- Remote contractor | micro1 application platform
- Experience
- Recorded experience: Proven hands-on experience in big data engineering, including building and maintaining large-scale data pipelines, with advanced Python proficiency and strong knowledge of distributed processing frameworks, relational and NoSQL databases, ETL, data modeling, and data warehousing
- Core expertise
- Data Engineering & Big Data | Big Data | Data Engineering | Data Pipelines
- Named tools
- Python | AWS | GCP
- Geographic eligibility
- Not specified beyond Remote
- Listing dates
- Posted 2026-09-16 | Valid through 2026-10-16
- Compensation
- Recorded compensation: $30-$80/hour
Responsibilities
- Design, build, and maintain scalable big data pipelines and architectures supporting robust data solutions.
- Collaborate with cross-functional teams to understand data requirements and deliver solutions aligned with 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, scalability, and reliability.
- Monitor and troubleshoot data systems to maintain high availability and performance.
- Identify opportunities to improve the scalability, reliability, and efficiency of data pipelines and infrastructure.
- Enforce data quality, security, and governance standards across data engineering solutions.
- Apply data modeling, ETL, and data warehousing principles to large-scale data systems.
- Document technical solutions and architectural decisions clearly.
- Communicate complex technical concepts effectively to technical and non-technical stakeholders.
- Apply professional big data engineering expertise as high-quality real-world input for next-generation AI systems.
Skills
Big DataData EngineeringPythonData PipelinesData ArchitectureData IntegrationData TransformationData ProcessingDistributed Data ProcessingHadoopApache SparkApache FlinkRelational DatabasesNoSQL DatabasesDistributed DatabasesDatabase OptimizationData ModelingETLData WarehousingData StorageData QualityData SecurityData GovernanceSystem MonitoringPerformance OptimizationAWSGoogle Cloud PlatformMicrosoft AzureMLOpsData Science WorkflowsTechnical Documentation
Requirements
- 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 database optimization and management techniques.
- Experience with distributed data processing frameworks such as Hadoop, Spark, or Flink.
- Strong foundation in data modeling and ETL processes.
- Strong understanding of data warehousing principles.
- Ability to design and maintain scalable, reliable, and high-performance data systems.
- Understanding of data quality, security, and governance practices.
- Excellent written and verbal communication skills with the ability to explain technical concepts to technical and non-technical stakeholders.
- Detail-oriented, proactive, and self-motivated approach to technical work.
- Ability to work effectively in a remote and autonomous environment.
- Experience in fast-paced or startup-like environments supporting global teams is preferred.
- Experience with cloud-based big data platforms such as AWS, GCP, or Azure is preferred.
- Familiarity with machine learning operations and data science workflows is preferred.
Benefits
- Fully remote contractor opportunity.
- Compensation of $30–$80 per hour.
- Opportunity to apply large-scale data engineering expertise to next-generation AI training.
- Work involving scalable data pipelines, distributed processing, databases, ETL, and data architecture.
- Opportunity to work with modern big data technologies including Hadoop, Spark, Flink, and cloud platforms.
- Exposure to data quality, governance, MLOps, and data science workflows.
- Remote collaboration with cross-functional and global teams.
Before you apply
- Confirm that your location is eligible for the role.
- Confirm the employment or contract type.
- Verify the current compensation at the official source.
- Review the required skills and experience.
- Check that the listing is still open before applying.
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