Jobs 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.

Support and maintain physical access control systems across federal field sites. Administer and troubleshoot Gallagher and C•CURE PACS, Windows Server, SQL Server, databases, connectivity, and related hardware. Support deployments, automation, environment maintenance, and on-site issue resolution while documenting recurring problems and solutions. The role requires independent troubleshooting across hardware, software, networking, and infrastructure, along with customer-focused communication and technical support.

Designs, implements, and modernizes enterprise PKI and identity trust services for secure federal systems. Responsibilities include PKI architecture, certificate lifecycle automation, cloud infrastructure across AWS and Azure, DevSecOps, CI/CD, cryptographic key management, compliance with federal security standards, and performance monitoring. The role collaborates with security and engineering teams to support Zero Trust initiatives and highly regulated environments.

Implement and maintain enterprise PKI architecture for secure federal systems. Build CI/CD pipelines, automate Windows and Linux infrastructure provisioning, manage Docker and Kubernetes workloads, administer AWS infrastructure, operate Hardware Security Modules, and support certificate lifecycle management. The role requires collaboration across application development, cloud infrastructure, identity, security, and compliance domains in highly regulated environments.

Design and lead end-to-end, secure, scalable application and integration architectures for federal modernization projects. Translate requirements into architecture strategies, guide API and cloud designs, evaluate tradeoffs, mentor teams, and ensure solutions meet security, compliance, and performance needs.

Design, build, and maintain scalable ETL/ELT data pipelines and analytical platforms on AWS and Databricks. Migrate legacy workflows to cloud-native services, implement data lake and catalog solutions, enable AI/RAG/vector search, ensure FedRAMP/NIST compliance, optimize performance, and mentor junior engineers while collaborating in Agile teams.

Lead QA activities for an IAM program: design and implement QA methodologies, create and run manual and automated tests, perform code/product reviews, triage defects, validate functionality/performance/security, and support CI/CD, UAT, and release validation across Agile teams.

The Lead AI/ML Engineer evaluates emerging technologies, leads teams in adopting solutions, and provides technical leadership while mentoring junior specialists.