• Responsible for building and maintaining scalable, high-performance data solutions using Azure Databricks, Apache Spark, AKS, Airflow, Postgres, and modern data lakehouse architectures. • Play a key role in the full software development lifecycle—from design and implementation to deployment and documentation. • Collaborate cross-functionally to support analytics, reporting, and operational data needs. • Ensure data quality, governance, and compliance through validation, documentation, and secure practices. • Contribute to and enforce best practices in data engineering, including version control (Git), CI/CD pipelines, and coding standards.

Title: Data Architect Clearance Required: TS/SCI   Location: Remote and Occasional travel to Arlington, VA Position Type: Full-Time  About the company:   At VivSoft, we aim to solve complex federal problems using emerging and open technologies in a collaborative and rewarding environment. VivSoft is a diverse team of strategists, engineers, designers, and creators experienced in building high performance effective softwares, with impactful organizational design and organizational dynamics for software delivery. We build secure Software Factories based on DoD reference designs and NIST Frameworks for Cloud and DevSecOps. These factories deliver AI/ML Applications, Data Science Platforms, Blockchain and Microservices for DoD, Healthcare and Civilian Agencies Job Summary: We are seeking a strategic and technically driven Data Architect to lead the design and governance of enterprise data architecture supporting advanced analytics and AI/ML mission needs. This role is responsible for architecting scalable data integration frameworks, enabling AI/ML data pipelines, and ensuring secure, high-quality, and interoperable data across cloud environments. The ideal candidate will bring deep expertise in data architecture, governance, and Zero Trust-aligned security principles, supporting complex data-sharing and analytics use cases in a compliant, mission-focused environment. Key Responsibilities: - Define and maintain enterprise Data Architecture Framework aligned to mission needs - Lead the design of data integration layers, including ingestion, transformation, and access patterns - Enable AI/ML architectures by supporting data pipelines, feature engineering, and model lifecycle processes - Establish and enforce data governance policies, including data classification, access control, and lifecycle management - Ensure compliance with Zero Trust architecture and RMF security principles - Support interoperability across internal and external systems through standardized data sharing approaches - Provide subject matter expertise for data integration, analytics, and mission use cases - Align data architecture with API strategies and broader enterprise architecture standards ​​​​​​​Required Skills: - 5+ years of experience in data architecture, data engineering, or analytics platforms - Experience designing enterprise data architectures and integration pipelines in cloud environments (AWS, Azure, or GCP) - Experience supporting AI/ML or advanced analytics platforms - Experience with large-scale data integration across multiple domains - Experience supporting DoD or Federal environments - Bachelor’s degree in Computer Science, Data Science, Engineering, or related field - Relevant cloud or data certifications (AWS, Azure, GCP, or CDMP)   Benefits:   - Comprehensive Medical, Dental, and Vision Plans (Healthcare benefits are 100% employer-paid for employees only)   - Life Insurance   - Paid Time Off (Flexible/Combined PTO, Bereavement Leave, 11 Company Paid Holidays)   - 401K Retirement Plan with employer match   - Professional Development Training Reimbursement

• Analyze and organize raw data • Build data systems and pipelines • Evaluate business needs and objectives • Interpret trends and patterns • Conduct complex data analysis and report on results • Prepare data for prescriptive and predictive modeling • Build algorithms and prototypes • Combine raw information from different sources • Explore ways to enhance data quality and reliability • Identify opportunities for data acquisition • Develop analytical tools and programs. • Collaborate with data scientists and architects on several projects.

• Design, build, and maintain scalable data solutions across modern cloud data platforms. • Develop robust data pipelines, managing ETL and ELT processes, optimising data storage and compute. • Implement architectures that enable reliable analytics and AI use cases. • Operate in a client-facing environment, translating business needs into technical solutions.