Millennium

• Serve as the lead Enterprise Architect, developing, maintaining, and presenting enterprise architecture • Develop and maintain architectural artifacts using the DoD Architecture Framework (DoDAF) • Design and manage the DoDAF Meta Model (DM2) • Review, evaluate, and approve architecture artifacts supporting Navy IT Enterprise initiatives • Define enterprise architecture methodologies, standards, tools, and processes • Develop end-to-end system integration architectures that support cloud modernization, interoperability, and enterprise-wide technical solutions • Coordinate with program leadership, engineering teams, cybersecurity stakeholders, and government representatives

• Create Audit Strategy and Audit Plan documents • Investigate how to perform audits for audit compliance • Create/Maintain Audit Strategy • Provide Audit Compliance Milestones to Scheduler • Report on existing auditing (Business Intelligence Advana/Jupiter) • Perform Fit/Gap analysis of audit procedures • Lead Audit meetings with Navy International Program Office • Ensure Audit Requirements are met

• Serve as the primary technical authority responsible for coordinating and integrating various networks • Ensure all technical elements are integrated to meet performance, security, and mission requirements • Provide technical leadership for system integration activities • Coordinate closely with other key personnel and government stakeholders • Identify and resolve integration issues • Manage technical discrepancies and ensure interoperability across all systems

• Develop cybersecurity policy and provide RMF support for the deployment of Storage and Compute, Network Transport, User Support, and Cyber Security in a cloud environment in support of the US Army • Oversee the delivery of continuous monitoring tools and capabilities • Drive the alignment of the US Army CSSP activities, priorities, and objectives

Full‑Stack data engineer We are seeking a highly self‑sufficient, motivated engineer based with strong full‑stack data engineering skills to join our innovative, dynamic team. This is a remote/offshore role that requires autonomy, excellent communication, and the ability to deliver high‑quality work with limited supervision while collaborating with a predominantly US‑based team. You will build reliable, scalable data products and user experiences that power AI/ML modeling, agentic workflows, and reporting—working end‑to‑end from data ingestion and transformation through to UI. Our Python‑based data platform is undergoing a major evolution toward a modern, cloud‑native ELT architecture. We are standardizing on Snowflake as our central data platform and dbt as our core transformation framework, implementing scalable, maintainable ELT practices that simplify ingestion, modeling, and deployment. This role will be pivotal in independently designing and building robust data pipelines and semantic layers that directly power our AI and machine learning initiatives—delivering clean, reliable, and well‑modeled data assets to our data science team for feature engineering, model training, and production inference. You will collaborate closely (primarily via remote channels) with data scientists and ML engineers to ensure our data ecosystem is optimized for experimentation speed, model performance, and seamless integration into downstream products and services. Key Responsibilities - Remote collaboration & communication: Operate effectively as an offshore member of a distributed team, proactively communicating status, risks, and blockers across time zones and coordinating overlap with US working hours as needed. - Full‑stack data engineering: Build across the entire stack, including data ingestion/acquisition and transformation, APIs, front‑end components, and automated test suites, delivering production‑grade solutions with minimal hand‑holding. - Autonomous delivery & ownership: Take end‑to‑end ownership of features and projects—clarifying requirements, breaking work into milestones, estimating timelines, and delivering high‑quality, well‑documented solutions. - Specification and design: Translate short‑ and long‑term business requirements, architectural considerations, and competing timelines into clear, actionable technical specifications and design documents. - Code quality: Write clean, maintainable, efficient code that adheres to evolving standards and quality processes, including unit tests and isolated integration tests in containerized environments. - Continuous improvement: Contribute to agile practices and provide input on technical strategy, architectural decisions, and process improvements, continuously suggesting better tools, patterns, and automation. Required Skills & Experience - Professional experience: 5+ years in software engineering, with a full‑stack background building complex, scalable data‑engineering pipelines using data warehouse technology, SQL with dbt, Python, AWS with Terraform, and modern UI technologies. - Modern data engineering: Strong experience with medallion data architecture patterns using data warehouse technologies (e.g., Snowflake), data transformation tooling (e.g., dbt), BI tooling, and NoSQL data marts (e.g., Elasticsearch/OpenSearch). - Testing and QA: Solid understanding of unit testing, CI/CD automation, and quality assurance processes for both data pipeline testing and operational data quality tests. - Remote work & autonomy: Proven track record working in a remote or distributed environment, demonstrating self‑motivation, reliable execution, and the ability to make sound technical decisions independently. - Agile methodology: Working knowledge of Agile development practices and workflows (e.g., sprint planning, stand‑ups, retrospectives) in a distributed team setting. - Education: Bachelor’s or Master’s degree in Computer Science, Statistics, Informatics, Information Systems, or a related quantitative field. Preferred Skills & Experience - Machine learning and AI: Hands‑on experience with large language models (LLMs) and agentic frameworks/workflows. - Search and analytics: Familiarity with the ELK stack (Elasticsearch, Logstash, Kibana) for search and analytics solutions. - Cloud expertise: Experience with AWS cloud services; familiarity with SageMaker; and CI/CD tooling such as GitHub Actions or Jenkins. - Front‑end expertise: Experience building user interfaces with Angular or a modern UI stack. - Financial domain knowledge: Broad understanding of equities, fixed income, derivatives, futures, FX, and other financial instruments.

• Assume responsibility for designing, implementing, and managing cloud-based networks and systems. • Ensure reliability, security, and efficiency of cloud infrastructure. • Collaborate with development and operations teams to optimize network performance and supports cloud-based applications and services.

• Provide engineering support (with a focus on macOS) for the deployment, integration, scaling, and maturation of the client's cloud environment for the enterprise, operational, and tactical networks. • Assume responsibility for the performance, design, configuration, and testing of complex large-scale cloud networks. • Support configuration and change management processes for Azure and Apple Environments. • Assume responsibility of macOS deployment (in an Intune environment).

• Collect program and project information for comprehensive Business Case Analyses • Conduct analyses of business processes for improvement • Gather and analyze data on trends impacting business operations • Develop detailed business cases for project and program initiatives • Prepare After Action reports on project outcomes • Monitor project progress and performance metrics

• Provide engineering support (with a focus on macOS) for the deployment, integration, scaling, and maturation of the client's cloud environment for the enterprise, operational, and tactical networks. • Assume responsibility for the performance, design, configuration, and testing of complex large-scale cloud networks. • Support configuration and change management processes for Azure and Apple Environments. • Assume responsibility of macOS deployment (in an Intune environment).

• Provide network engineering support (with a focus on transport) for the continued deployment and maturation of the US Army’s cloud environment for the enterprise, operational, and tactical networks. • Serve as the principle transport SME for the US Army’s enterprise transport activities. • Experience analyzing the impacts from existing DoW and Army policies on the implementation as well as those impacts to the Army’s security posture posed by the transport solutions. • Experience developing and / or analyzing IT Architecture design plans in support of the deployment of transport solutions for US Army Enterprise Network. • Familiarity with Zero Trust concepts and the impact that transport has on security posture, compliance, and governance. • Experienced with the performance, design, configuration, and testing of complex large-scale cloud networks. • Experienced with supporting configuration and change management processes for Azure and Google environments. • Experienced with system integrations of multivendor environments. • Experienced with planning and monitoring the deployment of Secured Cloud Solutions. • Experience with supporting an IT Project / Program Manage Office to include reporting requirements, enterprise planning, budgeting, and performance assessments. • Familiar with process improvement to optimize program management operations in support of the planning, implementation, and oversight of transport solutions and their integration into existing Army infrastructure. • Familiar with data-driven assessments as part of validation / program optimization activities. • Capable of facilitating stakeholder engagement and lead planning or change management initiatives. • Capable of developing and communicating plans to stakeholder community.