Data Engineer and Python Developer

Position Overview

We are seeking a highly skilled Data Engineer and Python Developer with strong analytical and development capabilities to support large-scale data initiatives. The ideal candidate will have experience in data analysis, ETL development, and AWS data engineering, with the ability to bridge both analysis and hands-on coding tasks. Experience working with Fannie Mae, Freddie Mac, or Capital One is highly preferred. This is a hybrid position requiring periodic on-site collaboration in Virginia.

Key Responsibilities

• Analyze large datasets to extract insights, identify patterns, and support data-driven decisions.
• Design, develop, and maintain ETL pipelines using Python and SQL.
• Build and optimize data workflows leveraging AWS services such as Glue ETL, Redshift, and S3.
• Collaborate with business and technical teams to define requirements, validate data, and deliver actionable outputs.
• Support data modeling, data transformation, and data quality assurance activities.
• Participate in performance tuning, troubleshooting, and deployment of data processes.
• Communicate effectively with cross-functional teams and stakeholders to ensure successful delivery of data initiatives.

Required Qualifications

• Bachelor’s degree in Computer Science, Information Systems, or a related field.
• 3–7 years of hands-on experience as a Data Engineer, Python Developer, or Data Analyst.
• Strong proficiency in Python and SQL for building ETL processes and automating data workflows.
• Solid understanding of AWS cloud services, especially Glue ETL, Redshift, and S3.
• Experience with data analysis and reporting for business insights.
• Excellent communication and problem-solving skills.

Preferred Qualifications

• Past experience with Fannie Mae, Freddie Mac, or Capital One in a data engineering or analytics capacity.
• Exposure to data governance, metadata management, or data quality frameworks.
• Familiarity with Git, Airflow, or other workflow orchestration tools.