Compunnel
Python + PySpark - Junior Developer
Compunnel - New York, New York, us, 10261
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Overview
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Overview
The Python + PySpark Junior Developer will be responsible for developing scalable data solutions using PySpark and Python. The role requires hands-on experience in data engineering, SQL, and cloud platforms such as AWS or Azure. The candidate should have strong problem-solving skills and experience in building efficient ETL pipelines for large-scale data processing.
Key Responsibilities
Develop and maintain data processing pipelines using Python and PySpark Design and implement ETL workflows for structured and unstructured data Optimize data storage, retrieval, and transformation processes Work with cloud platforms (AWS or Azure) to deploy and manage data solutions Write complex SQL queries for data transformation and analysis Collaborate with data engineers, analysts, and stakeholders to ensure data integrity and reliability Troubleshoot and resolve performance issues in data pipelines Required Qualifications
5+ years of experience in data engineering Strong proficiency in Python and object-oriented programming Hands-on experience with PySpark for large-scale data processing Proficiency in SQL for data manipulation and query optimization Experience with cloud platforms (AWS or Azure) Knowledge of ETL processes and data warehousing concepts Experience with Hadoop is acceptable Preferred Qualifications
Experience in optimizing Spark jobs for performance and efficiency Familiarity with DevOps practices for data engineering Understanding of data governance and security best practices
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Develop and maintain data processing pipelines using Python and PySpark Design and implement ETL workflows for structured and unstructured data Optimize data storage, retrieval, and transformation processes Work with cloud platforms (AWS or Azure) to deploy and manage data solutions Write complex SQL queries for data transformation and analysis Collaborate with data engineers, analysts, and stakeholders to ensure data integrity and reliability Troubleshoot and resolve performance issues in data pipelines Required Qualifications
5+ years of experience in data engineering Strong proficiency in Python and object-oriented programming Hands-on experience with PySpark for large-scale data processing Proficiency in SQL for data manipulation and query optimization Experience with cloud platforms (AWS or Azure) Knowledge of ETL processes and data warehousing concepts Experience with Hadoop is acceptable Preferred Qualifications
Experience in optimizing Spark jobs for performance and efficiency Familiarity with DevOps practices for data engineering Understanding of data governance and security best practices
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