• Design, build, and optimize ETL/ELT data pipelines using Azure and GCP services • Develop and maintain optimized data models within multi-cloud data warehouse solutions • Monitor and optimize the performance of data warehouse queries • Collaborate with Data Scientists to design feature stores and pipelines for ML models • Implement workflows to automate the end-to-end data lifecycle for AI/ML processes • Work with Data Science teams to deploy and manage machine learning models in production environments • Write complex SQL queries and develop scripts in Python for data manipulation

• Assist the Chief Engineer by leading the implementation, scaling, and day-to-day maturity of enterprise-wide CI/CD pipelines. • Evaluate, prototype, and integrate emerging DevSecOps tools, automated security scanning, and container hardening techniques to optimize the Cloud One ecosystem. • Implement and maintain complex Infrastructure as Code (IaC) and Configuration as Code (CaC) scripts tailored for DoD Impact Levels (IL) 2, 4, 5, and 6. • Support the Chief Engineer in reviewing cloud configurations across AWS, Azure, GCP, and OCI to ensure alignment with security and resiliency goals. • Assist in embedding automated configuration monitoring and continuous Authorization to Operate (cATO) strategies into the delivery pipeline to meet RMF and STIG requirements. • Serve as the tactical, hands-on mentor for cross-functional DevOps and engineering teams, translating the Chief Engineer's high-level strategy into technical reality.

• Configure, maintain, and optimize Identity Provider (IdP) solutions to ensure secure single sign-on (SSO) and access management capabilities. • Manage and support Active Directory (AD) and Lightweight Directory Access Protocol (LDAP) environments, ensuring proper schema management, synchronization, and access controls. • Develop, integrate, and maintain continuous integration and continuous deployment (CI/CD) pipelines to automate infrastructure and application deployment. • Utilize identity data virtualization tools to integrate complex, disparate identity repositories.

• Work closely with customer stakeholders, scientists, and IT professionals to deliver Compute at Scale • Develop, evolve, and administer HPC platforms along with support for Scientific applications, workflows, and other related infrastructure both on-prem and Cloud hosted • Drive architecture, roadmaps, and execution of projects to establish and operate IT infrastructure best practices for customers • Full stack support - design and evolution of platforms, application administration, supporting customer workflows, profiling and performance tuning • Monitoring and maintenance of scoped systems, platform and systems administration, troubleshooting hardware, software, and networking related issues • Solution architecting and hands-on engineering (on-prem + Cloud) • Documentation • Collaborating with cross-discipline team members and customers • Supporting internal and customer Architecture and Design efforts • Supporting customers with their workflow pipelines (advisory and hands-on) • Comprehensively documenting new and existing computational assets • Maintaining the flexibility to pivot as engagement scopes may evolve • Support for AWS & GCP Cloud applications, migrations, and modernization • CloudOps / IaC for on-going platform management • Setup and configuration of AWS & GCP Cloud infrastructure for new platform builds • Ensuring system compliance with company security standards and applicable regulatory requirements • Transition support for modernized services to operational teams • Provide engineering level troubleshooting and services restoration for operational issues as they arise on supported platforms • Provide training/mentorship for junior level team members • Escalation point on multiple engagements to ensure resolution