Python Backend Developer with AWS

Position: Python Backend Developer with AWS Location: McLean, VA (Preferred) | Richmond, VA | Plano, TX Duration: Long term contract Note: Ex–Capital One candidates preferred, especially those able to work at client locations. Role Overview: Capital One is seeking a skilled Backend Developer with strong Data Engineering expertise to design, build, and maintain scalable data pipelines in a cloud-native environment. This role focuses on backend development using Python, PySpark, and AWS, supporting high-volume data processing and analytics platforms. The ideal candidate has hands-on experience building production-grade data pipelines, working with distributed data frameworks, and deploying solutions on AWS. Key Responsibilities • Design, develop, and maintain backend data pipelines using Python and PySpark • Build and optimize ETL/ELT workflows for large-scale data processing • Develop cloud-hosted solutions using AWS services • Ensure performance, reliability, and scalability of data engineering pipelines • Collaborate with product owners, data scientists, and platform teams to support analytics and business use cases • Implement data quality checks, logging, monitoring, and error handling • Participate in code reviews and follow Capital One engineering best practices • Support deployment and operations in a CI/CD-driven cloud environment Required Skills & Qualifications • Strong hands-on experience with Python backend development • Solid experience using PySpark for large-scale data processing • Experience hosting and deploying applications on AWS (e.g., S3, EC2, EMR, Glue, Lambda, CloudWatch – exact services may vary) • Proven experience building data engineering pipelines • Understanding of distributed systems and data processing concepts • Experience working in Agile/Scrum development environments • Strong problem-solving and debugging skills Preferred Qualifications • Ex–Capital One experience (highly preferred) • Ability to work onsite in McLean, VA Experience with: • CI/CD pipelines • Data lake architectures • Cloud-native backend systems • Financial services or enterprise-scale data platform experience Nice-to-Have Skills • SQL and data modeling • Workflow orchestration tools (Airflow or similar) • Exposure to streaming or near–real-time data processing • Knowledge of security and compliance in cloud environments