Senior PySpark Data Engineer

As a Data Engineer, you will be responsible for designing, developing, and maintaining data solutions for data generation, collection, and processing in Big Data environment using predominantly PySpark/Python. Your typical day will involve creating data pipelines, ensuring data quality, and implementing ETL processes to migrate and deploy data across systems using PySpark. Responsibilities Design, develop, and maintain robust, scalable high-performance Data Pipelines using PySpark. Create data pipelines, ensuring data quality, and implement ETL processes to migrate and deploy data across systems. Migrate Ab Initio ETL Applications into Pyspark based data pipelines. Migrate On Prem workloads into Cloud (AWS, Databricks, Snowflake) based on use cases. Collaborate with cross-functional teams to identify and resolve data-related issues. Stay updated with the latest advancements in data engineering and integrate innovative approaches for sustained competitive advantage. Qualifications 8+ years of professional experience in Hadoop, PySpark/Python development. Proven expertise in PySpark and experience in handling huge volume of data. 3+ years of working experience in AWS, Databricks/Snowflake, Airflow. Familiarity with CI/CD pipelines and version control systems (e.g., Git). Strong debugging and problem-solving skills. Excellent communication and collaboration skills. Good to Have Skills AWS EKS Experience, Dockers and Containers. #J-18808-Ljbffr