3+ years of experience in data and automation engineering with a strong focus on Python.
3+ years of experience developing, maintaining, and administrating SQL databases.
2+ years of experience with cloud-based data platforms like Databricks and Apache Airflow.
Experience designing, testing, and deploying robust ETL workflows.
U.S. citizenship with the ability to pass a background investigation; DHS clearance preferred.
Responsibilities
Design, develop, and maintain robust ETL pipelines for data integration.
Refactor existing code and automated processes into Python, validating through tests and user feedback.
Implement scalable data solutions using Python and cloud platforms like Databricks and Apache Airflow.
Collaborate with data scientists and analysts for seamless data accessibility.
Optimize data architecture and workflows for efficiency and security.
Troubleshoot data pipeline issues to ensure data integrity.
Benefits
401(k) plan and contributions
Medical, dental, and vision insurance
Life and disability insurance
Flexible spending account
Paid time off
Professional development opportunities
Employee assistance program
Focus on work-life balance
Full Job Description
Pay: $110,000 - $125,000 per year
Job Description: Python Developer - Hybrid
The Python Developer is responsible for designing, developing, and implementing Python based automation to execute the reconciliation process. They are responsible for building robust, scalable ETL data pipelines that extract, transform, and load data from multiple sources into an integrated platform. This role develops, tests, and deploys Python automation scripts and workflows, ensuring accuracy, efficiency, and reliability throughout the reconciliation lifecycle. Working within cloud and enterprise data environments, they collaborate closely with technical leads and stakeholders to translate requirements into well-architected, maintainable solutions and continuously enhance automation performance.
Key Responsibilities:
Design, develop, and maintain robust ETL pipelines for data integration across multiple sources.
Refactor existing code and automated processes into Python, validating functionality through detailed test cases and user feedback.
Implement scalable data solutions using Python and cloud-based platforms such as Databricks and Apache Airflow.
Collaborate with data scientists and analysts to ensure seamless data accessibility and usability.
Optimize data architecture and workflows to enhance efficiency, performance, and security.
Troubleshoot data pipeline issues and ensure data integrity across systems.
The ideal candidate must have the following experience, background, and credentials:
3+ years of experience in data and automation engineering with a strong focus on Python.
3+ years of experience developing, maintaining, and administrating SQL databases.
2+ years of experience working with cloud-based data platforms such as Databricks, Apache Airflow, or other AWS services (e.g. Lambda, S3).
Experience designing, testing, and deploying robust ETL workflows and integrate with enterprise data systems.
Be a U.S. citizen able to pass a background investigation by the client agency. DHS clearance with CBP/ICE, or DoD Top-Secret preferred.
Preferred Skills:
Experience with Optical Character Recognition (OCR) and Document Understanding frameworks (e.g., AWS Textract, Tesseract, or layout-aware models)
Familiarity with DevOps practices such as version control, CI/CD, and containerized deployment.
Job Type: Full-time
Work Location:Hybrid (Washington, DC)
Experience:
Python: 3 years (Required)
Benefits:
401(k)
401(k) contribution
Medical insurance
Dental insurance
Vision insurance
Life & Disability Insurance
Flexible Spending Account
Paid time off
Professional development
Employee assistance program
Work-life balance
Application Question(s):
This position requires U.S. citizenship. Are you a U.S. citizen?
