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ETL/Data Engineer - Remote Work

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Summary

Design, develop, and maintain scalable ETL pipelines and data architectures using SQL, Python, and cloud-based data platforms to transform raw data into actionable business insights.

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Overview of the Role

The ETL/Data Engineer will design and implement sophisticated data processing systems and ETL pipelines, transforming raw data into actionable business insights through advanced technical expertise and strategic data architecture.

Key Responsibilities:

  • Designing, developing, and maintaining scalable ETL pipelines and data processing systems with advanced technical proficiency.
  • Building and optimizing data architectures that support efficient data extraction, transformation, and loading processes.
  • Implementing data quality checks and monitoring systems to ensure accuracy and reliability.
  • Collaborating with data analysts and business teams to understand requirements and deliver solutions.
  • Optimizing data storage and retrieval processes for improved performance and cost-effectiveness.
  • Troubleshooting and resolving complex data pipeline issues while maintaining system stability.

Requirements:

  • Experience: 3+ years in ETL development, data engineering, or related fields
  • Programming: Strong knowledge of SQL, Python, and data processing frameworks
  • Cloud Platforms: Experience with data warehousing concepts and cloud-based data platforms
  • Database Design: Understanding of data modeling and performance optimization
  • Version Control: Familiarity with version control systems and data pipeline orchestration tools
  • Data Quality: Knowledge of data quality assurance and monitoring best practices
  • Language: Advanced level of English
  • Flexibility: Choose where and how you work for enhanced creativity and innovation.
  • Tailored Compensation: Personalize your earnings to suit your financial goals.
  • Tech-Driven Tools: Access cutting-edge resources for seamless collaboration and productivity.
  • Autonomous Workflow: Take control of your schedule to achieve work-life balance.
  • Well-being: Enjoy generous leave policies for rest and rejuvenation.
  • Diversity & Inclusion: Thrive in a diverse and inclusive environment.
  • Collaboration: Engage with industry leaders for collective growth.
  • Development: Access mentorship and growth opportunities for continuous advancement.

Skills

See also

Data Engineering jobs by country — openings, pay and top skills →

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