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Data Engineer and Python Developer
Baltimore, MarylandPosition 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 (FNM), Freddie Mac, or Capital One is highly preferred.
This is a hybrid position requiring periodic on-site collaboration in Virginia.
Key Responsibilities
Required Qualifications
Preferred Qualifications
Soft Skills
Work Environment
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 (FNM), Freddie Mac, or Capital One is highly preferred.
This is a hybrid position requiring periodic on-site collaboration in Virginia.
- 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.
- 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.
- 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.
- Strong analytical mindset and attention to detail.
- Ability to balance multiple priorities and meet project deadlines.
- Effective communicator, capable of explaining technical concepts to non-technical stakeholders.
- Collaborative team player with a proactive, solution-oriented approach.
- Hybrid role – based in Virginia (VA) with periodic on-site presence.
- Collaborative team environment focused on quality, innovation, and continuous improvement.