Python Developer

Job Requirements Here is the cleaned version with extra gaps, special characters, bullets, and markdown formatting removed: JD#2 Data Engineer AWS Python PySpark Kafka Position Overview We are seeking an experienced Data Engineer to design, build, and maintain scalable data solutions on cloud-based platforms. The ideal candidate will have strong expertise in Snowflake, AWS, and modern data processing tools, with hands-on experience in Python, PySpark, and Kafka. This role involves close collaboration with business and technical teams to deliver reliable, high-quality data pipelines and data models. Key Responsibilities Design, develop, and optimize data tables and schemas in Snowflake to support analytical and reporting needs Build robust data ingestion and transformation pipelines using Python and PySpark Load, transform, and manage structured and semi-structured data within Snowflake Develop scalable data processing solutions leveraging AWS services Implement and support streaming or near-real-time data pipelines using Kafka Perform code reviews, unit testing, and follow data engineering best practices Load and validate historical data during initial builds and system migrations Conduct integration testing in collaboration with business stakeholders to ensure requirements are met Provide feedback on code changes and actively participate in the code review and testing process Monitor, troubleshoot, and optimize data pipelines for performance and reliability Required Skills and Qualifications 5+ years of experience in data engineering or related roles Strong hands-on experience with Snowflake, including table design, data loading, and optimization Proficiency in Python for data processing and pipeline development Experience using PySpark for large-scale data transformations Solid understanding of ETL and ELT concepts, data modeling, and data integration best practices Experience working with AWS cloud services for data platforms Preferred and Good-to-Have Skills Experience with Kafka or other streaming data technologies Familiarity with cloud-native data architectures and distributed systems Experience supporting analytical and enterprise data platforms Knowledge of data quality, monitoring, and performance tuning techniques Work Experience 7-10Years