About
Responsibilities
Utilize Python, PySpark, SQL, and other data wrangling tools to analyze and transform data into actionable insights.
Support the full data engineering lifecycle, from research and experimentation through implementation and deployment of scalable data pipelines and analytics solutions.
Conduct peer code reviews to ensure code quality, maintainability, and adherence to best practices.
Develop technical documentation and operational guidance for end users and stakeholders.
Perform data cleansing, integration, validation, and transformation activities to support analytical and reporting needs.
Design and implement data engineering solutions while serving as a bridge between technical teams and business stakeholders.
Monitor and optimize data system performance, reliability, and scalability.
Troubleshoot issues and improve data processing efficiency through code optimization and resource management.
Qualifications
Minimum of 3 years of hands‑on data engineering experience.
Experience supporting U.S. Federal Government clients is preferred.
Bachelor's degree from an accredited college or university.
Strong programming experience with Python, PySpark, and SQL.
Experience with data quality management, including data validation, cleansing, reconciliation, and error handling.
Knowledge of ETL processes, data ingestion, integration, and transformation techniques.
Experience working within Agile environments and utilizing tools such as Git, CI/CD pipelines, and test‑driven development methodologies.
Proven ability to ingest, engineer, transform, analyze, and visualize large datasets.
Ability to travel as needed to support project requirements.
Active U.S. Government Secret Clearance required.
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Languages
- English
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