Design, build, and maintain scalable ETL pipelines for large-scale data processing.
Implement PySpark-based data transformations and workflows.
Develop, manage, and optimize data pipelines with Databricks.
Optimize pipelines for performance, scalability, and cost efficiency.
Troubleshoot, debug, and resolve data processing issues.
Collaborate with cross-functional teams to deliver high-quality data solutions.

🎯 Requirements

5–7 years of professional data engineering experience.
Hands-on PySpark (intermediate–advanced).
Databricks experience including Autoloader and Python workflows.
Proven optimization of pipelines for performance and cost.
Strong ETL knowledge and large-scale data transformations.
Excellent problem-solving and cross-functional communication.

🎁 Benefits

100% Remote Work.
Competitive USD Pay.
Paid Time Off.
Work with Autonomy.
Work with Top American Companies.

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