Design, construct, and maintain the infrastructure and architecture required for large-scale data processing systems.
Develop and implement data pipelines, ETL processes, and data integration workflows to collect, transform, and deliver data from diverse data sources.
Build and maintain scalable data storage solutions, including data lakes, data warehouses, and cloud-based data platforms.
Collaborate with data scientists, analysts, and application developers to ensure data accessibility and usability for analytics and reporting.
Optimize data systems for performance, scalability, and reliability.
Implement data quality checks, validation processes, and monitoring to ensure data integrity.
Support the development and maintenance of data models and data architectures that align with business and analytical requirements.
Troubleshoot and resolve issues related to data pipelines, infrastructure, and system performance.
Maintain documentation for data architecture, workflows, and technical processes.
Stay current with industry trends, emerging technologies, and best practices in data engineering and data architecture.
Requirements
Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or related field
Minimum 8 years of professional experience in data engineering, data integration, or a related technical field, including 3+ years in a leadership role
Ability to document data flows, data dependencies, and technical processes in support of business process analysis
Experience supporting data-intensive, analytical, research, financial, or regulatory environments
Demonstrated experience designing, developing data pipelines, data transformations, and data workflows
Strong experience developing ETL/ELT pipelines and large-scale data processing solutions
Familiarity with data governance, data quality, metadata, and access control considerations
Proficiency with SQL and programming languages such as Python, Java, or Scala
Experience working with relational and/or non-relational databases and data storage technologies
Strong understanding of data modeling, data warehousing, and data integration concepts
Ability to support modernization or migration efforts from legacy data environments
Strong analytical and problem-solving skills
Excellent communication and collaboration abilities
Ability to work effectively in agile, hybrid, or iterative delivery environments, including collaboration with cross-functional teams and incremental solution delivery.
US Citizenship required.
Must reside in the Continental US; and be within driving distance to Washington, DC.
Depending on the government agency, specific requirements may include public trust background check or security clearance.