Richmond, VA- DATA ENGINEER

We are seeking a skilled and detail-oriented Data Engineer with strong expertise in Python, AWS, and PySpark to join our team as a 1099 Independent Contractor. The ideal candidate will be responsible for designing, building, and maintaining scalable data pipelines, ensuring data quality, and enabling advanced analytics and reporting across the organization. Key Responsibilities • Design, develop, and optimize ETL/ELT data pipelines using Python, PySpark, and AWS services. • Ingest, transform, and process large-scale datasets from various structured and unstructured sources. • Work with cloud-native tools (AWS Glue, Lambda, EMR, S3, Redshift, Athena, etc.) to manage data storage, transformation, and access. • Implement and maintain data models, schemas, and data lakes/warehouses. • Ensure data quality, reliability, and availability across all stages of the pipeline. • Collaborate with data scientists, analysts, and business teams to understand data requirements and deliver solutions. • Monitor pipeline performance, troubleshoot issues, and implement best practices for optimization and security. • Document processes, workflows, and data flows to support long-term scalability and team knowledge-sharing. Required Skills & Qualifications • Strong programming skills in Python for data manipulation and automation. • Hands-on experience with PySpark for big data processing. • Proficiency in AWS cloud services (S3, Glue, EMR, Redshift, Lambda, Athena, CloudWatch, etc.). • Experience with ETL/ELT workflows and data pipeline orchestration tools (e.g., Airflow, Step Functions). • Solid understanding of data modeling, warehousing, and data lake concepts. • Knowledge of SQL and experience working with relational and NoSQL databases. • Familiarity with CI/CD, version control (Git), and Agile development practices. • Strong problem-solving skills and the ability to work independently or within a team. Preferred Qualifications (Nice To Have) • Experience with containerization tools (Docker, Kubernetes). • Exposure to streaming technologies (Kafka, Kinesis). • Knowledge of data governance, security, and compliance in cloud environments. • Familiarity with BI/Analytics tools (Tableau, Power BI, QuickSight). Education Bachelors or Masters degree in Computer Science, Information Technology, Data Engineering, or a related field.