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etl python databricks data pipelines performance tuning📋 Description
- Design, build, and maintain scalable ETL pipelines for large-scale data processing.
- Implement data transformations and workflows using PySpark at an intermediate to advanced level.
- Work extensively with Databricks to develop, manage, and optimize data pipelines.
- Optimize pipelines for performance, scalability, and cost efficiency across environments.
- Troubleshoot, debug, and resolve data processing and pipeline issues.
- Collaborate with cross-functional teams to deliver high-quality data solutions.
🎯 Requirements
- 5–7 years of professional experience in data engineering.
- Strong hands-on proficiency with PySpark (intermediate to advanced).
- Solid experience working with Databricks, including Autoloader, Python-based workflows, and platform best practices.
- Proven experience optimizing data pipelines for performance and cost efficiency.
- Strong understanding of ETL processes and large-scale data transformations.
- Excellent problem-solving and ability to collaborate with stakeholders.
🎁 Benefits
- 100% Remote Work
- Competitive USD pay
- Paid Time Off
- Autonomy to manage your time
- Work with top American Companies
- Global, diverse team
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