Remote Data Engineer: ETL, Python & Data Quality
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Summary
Contract Data Engineer working fully remote (UK) who designs, builds, and maintains scalable ETL pipelines in Python, optimizes data workflows for performance and reliability, and champions data quality through validation and production troubleshooting. 10-40 hrs/week at $30-$90/hour.
- 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.
Type: Contract
Compensation: $30 - $90/hour
Location: Remote
Commitment: 10-40 hrs/week
Role 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.
- Have expert-level proficiency in Python programming.
- Have extensive hands-on experience building and maintaining ETL pipelines and data workflows.
- Have a proven ability to work independently in a fully remote environment.
- Possess exceptional written and verbal communication skills, with a strong focus on clarity and collaboration.
- Have a strong analytical and problem-solving mindset with acute attention to detail.
- Demonstrate expertise in debugging and optimizing large-scale data systems.
- Easy Apply on LinkedIn
- Check email for next steps
- Participate in resume evaluation & interview stage