Python-Pyspark Developer

Responsibilities :

We are looking for an experienced Python PySpark Developer to design, develop, and optimize large-scale data processing systems. The ideal candidate will work on big data platforms, build scalable ETL pipelines, and process high-volume datasets using Spark and Python. Key Responsibilities Data Engineering & Development Develop and maintain data pipelines using Python and PySpark Process and transform large datasets in distributed environments Build scalable ETL/ELT workflows Big Data Processing Work with Apache Spark (PySpark) for batch and real-time processing Optimize Spark jobs for performance and efficiency Handle structured and unstructured data Data Integration Ingest data from multiple sources: Databases (SQL/NoSQL) APIs Files (CSV, JSON, Parquet) Integrate with data platforms like: Hadoop (HDFS) Cloud (AWS, Azure, GCP) Performance Optimization Tune Spark jobs (partitioning, caching, parallelism) Optimize SQL queries and transformations Improve data processing efficiency and cost Collaboration & Support Work with data engineers, data scientists, and analysts Translate business requirements into technical solutions Participate in code reviews and agile development practices Monitoring & Troubleshooting Debug and resolve issues in data pipelines Monitor job execution and data quality Ensure reliability and availability of data workflows

Technical and Professional Requirements:

Primary skills:Python, Pyspark