Teams at Capital Technology Group

Leads the design, development, and maintenance of scalable AWS data platforms, pipelines, ETL/ELT workflows, data models, and orchestration systems. Uses Python, PySpark, SQL, dbt, AWS services, modern lakehouse technologies, and CI/CD practices to deliver secure federal data solutions. Responsibilities include platform modernization, performance optimization, AI-enabled data integration, compliance support, technical mentoring, architecture discussions, and cross-functional Agile collaboration.

Develop and implement quality strategies, automated testing frameworks, and validation practices for data pipelines and analytical datasets. Test accuracy, completeness, integrity, schema consistency, business rules, and freshness using Python, PySpark, SQL, Spark, Airflow, and AWS. Investigate data anomalies and pipeline failures, monitor quality metrics, support CI/CD and releases, and collaborate with engineers, analysts, data scientists, and stakeholders to ensure reliable financial and regulatory data.

Design, develop, test, and maintain secure, scalable software applications and backend services for federal modernization initiatives. Build Java and Groovy services, REST and GraphQL APIs, database integrations, and distributed systems. Collaborate with engineering, DevSecOps, infrastructure, product, and delivery teams while contributing to CI/CD, automated testing, cloud adoption, troubleshooting, documentation, and application modernization.