Data Engineer - Software Prototyping

📍 Job Overview

Job Title: Data Engineer - Software Prototyping

Company: Invictus International Consulting, LLC

Location: Reston, VA

Job Type: FULL_TIME

Category: Data Engineering / Software Development

Date Posted: 2026-10-06

Experience Level: Mid-Level (2-5 years)

Remote Status: On-site

🚀 Role Summary

• Design, develop, and deploy software prototypes and data management tools to support intelligence operations, focusing on CI/HUMINT missions.

• Implement robust data ingestion pipelines, AI/ML algorithms, and secure cross-system data exchange capabilities within intelligence community environments.

• Translate complex operational requirements into functional, scalable, and secure software solutions, collaborating with diverse technical and operational stakeholders.

• Drive innovation through modern software development practices, cloud-based environments, API design, and automated testing frameworks to enhance intelligence capabilities.

📝 Enhancement Note: While the title is "Data Engineer - Software Prototyping," the description strongly emphasizes software engineering principles, tool development, and API creation within an intelligence context. This suggests a hybrid role where data engineering skills (pipelines, AI/ML integration) are crucial, but the primary output is functional software prototypes and capabilities. The "Software Prototyping" aspect indicates a focus on rapid development, iteration, and demonstrating new functionalities for intelligence applications.

📈 Primary Responsibilities

• Provide comprehensive technical development support for CI/HUMINT software prototypes and advanced data management capabilities.

• Serve as a key technical resource for designing, developing, and deploying tools that enhance intelligence operations, working closely with Data Management Support Officers and Data Scientists.

• Translate operational requirements into functional software solutions, ensuring alignment with mission objectives and technical feasibility.

• Develop and implement data ingestion pipelines to collect, process, and integrate diverse data sources for analysis and operational use.

• Support the development and deployment of AI/ML algorithms in collaboration with Data Scientists, integrating them into functional prototypes and operational tools.

• Conduct thorough code reviews to ensure adherence to quality, security, and performance standards within a classified environment.

• Develop APIs and interfaces to enable seamless cross-system data exchange and interoperability within the intelligence community.

• Implement automated testing frameworks and CI/CD pipelines to ensure code quality, rapid deployment, and continuous improvement of software prototypes.

• Coordinate with Data Management Tool Administrators on system enhancements, user support, and data integrity.

• Interface with the IT Project Manager on technical development activities, project timelines, and resource allocation.

• Coordinate with the Information System Security Engineer (ISSE) on security requirements, implementation, and compliance.

• Support the development of software solutions for secure cross-domain data transfer capabilities.

📝 Enhancement Note: The responsibilities highlight a strong software engineering focus, particularly in prototyping and developing intelligence tools. The data engineering aspect is integrated through data ingestion, AI/ML integration, and data management support, emphasizing the practical application of these skills within a software development lifecycle for specific intelligence use cases.

🎓 Skills & Qualifications

Education:

• Bachelor's degree from an accredited institution in a field applicable to the position (e.g., Computer Science, Software Engineering, Data Science, Information Technology, or a related technical discipline).

• An additional four (4) years of directly related technical experience may be substituted in lieu of a degree, aligning with the minimum experience requirement. Experience:

• Minimum of four (4) years of directly related technical experience in software engineering, data engineering, or a closely related field.

• Proven experience in developing and deploying software prototypes and data management solutions.

• Demonstrated experience working within secure intelligence environments and adhering to strict security protocols. Required Skills:

• Expertise in modern software development practices, including Agile methodologies.

• Proficiency in multiple programming languages relevant to data engineering and software development (e.g., Python, Java, C++, Go).

• Strong understanding and practical experience with cloud-based development environments (e.g., AWS, Azure, GCP, or specific government cloud platforms).

• Demonstrated ability in API design, development, and integration for data exchange and system interoperability.

• Experience with automated testing frameworks and implementing CI/CD pipelines for efficient software delivery.

• Solid understanding of data ingestion pipelines, ETL/ELT processes, and data integration technologies.

• Familiarity with AI/ML concepts and experience integrating algorithms into software applications.

• Knowledge of cross-system interoperability challenges and solutions within complex IT architectures.

• Experience conducting thorough code reviews to ensure code quality, security, and performance.

• Familiarity with intelligence community data standards and security protocols.

• Excellent communication skills for effective collaboration with multidisciplinary teams and diverse stakeholders. Preferred Skills:

• Experience with specific government security accreditation processes (e.g., RMF).

• Familiarity with specific intelligence community tools and data formats.

• Experience with containerization technologies (e.g., Docker, Kubernetes).

• Knowledge of cybersecurity principles and best practices for secure software development.

• Experience with data visualization tools and techniques.

📝 Enhancement Note: The requirements emphasize a blend of software engineering and data engineering skills, with a strong emphasis on security and intelligence community context. The "applicable to the position" phrasing for the degree suggests flexibility for related technical fields, but practical experience is paramount. The substitution clause for the degree is a key detail for candidates with extensive experience but potentially non-traditional academic backgrounds.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Showcase examples of developed software prototypes, demonstrating functionality and problem-solving capabilities.

• Include case studies detailing the design and implementation of data ingestion pipelines or data integration solutions.

• Present examples of API development, highlighting design patterns, documentation, and integration success.

• Demonstrate experience with automated testing and CI/CD implementations, illustrating efficiency gains and quality improvements.

• Provide evidence of working with cloud-based development environments and deploying applications within them. Process Documentation:

• Document workflows for translating operational requirements into technical specifications and software designs.

• Illustrate processes for conducting code reviews, ensuring adherence to security and quality standards.

• Detail methodologies for implementing and testing data ingestion pipelines and AI/ML model integration.

• Explain processes for developing and maintaining APIs for cross-system data exchange.

• Outline strategies for implementing and managing CI/CD pipelines and automated testing frameworks.

📝 Enhancement Note: For a role focused on prototyping and intelligence applications, a portfolio should highlight practical application of skills. Emphasis should be placed on demonstrating the ability to build functional tools, integrate data, and ensure security and interoperability, rather than purely theoretical data models. The ability to explain the process behind these achievements is as critical as the outcome itself.

💵 Compensation & Benefits

Salary Range: $160,000 - $165,000 USD per year.

Benefits:

• Comprehensive health, dental, and vision insurance.

• Retirement savings plan with company match (e.g., 401k).

• Paid time off (PTO), including vacation, sick leave, and holidays.

• Professional development opportunities, including training and certifications.

• Potential for performance-based bonuses and incentives.

• Life insurance and disability coverage.

• Support for obtaining and maintaining security clearances and polygraphs. Working Hours:

• Standard full-time work schedule, typically 40 hours per week.

• Potential for occasional overtime to meet project deadlines or operational demands.

• Flexibility may be offered depending on project needs and team coordination, but the role is primarily on-site.

📝 Enhancement Note: The provided salary range is specific and competitive for a mid-level Data Engineer/Software Prototyper with TS/SCI clearance in the Reston, VA area. Benefits are standard for a full-time role in the government contracting sector, with particular emphasis on support for clearance requirements.

🎯 Team & Company Context

🏢 Company Culture

Industry: Government Contracting / Technology Services / National Security. Invictus International Consulting, a Red River company, specializes in providing technology and services that support government and national security missions, particularly within the intelligence community. They focus on advanced modernization, cybersecurity, intelligence, and systems integration.

Company Size: Invictus International Consulting is part of Red River, which is a significant player in the IT solutions and services market. Red River is considered a mid-to-large enterprise, implying Invictus benefits from the resources and stability of a larger organization while maintaining specialized focus.

Founded: Invictus International Consulting's founding date is not explicitly provided, but its acquisition by Red River (founded in 1993) suggests a history of established operations and expertise in government and defense sectors.

Team Structure:

• The Data Engineer will be part of a technical development team focused on software prototyping for intelligence operations.

• This team likely includes Data Management Support Officers, Data Scientists, Information System Security Engineers (ISSEs), and potentially IT Project Managers.

• Collaboration is expected to be close and multidisciplinary, requiring effective communication across different technical specializations and operational roles.

• The engineer will report to a technical lead or project manager within the software prototyping division. Methodology:

• The team likely operates using Agile development methodologies, emphasizing iterative development, collaboration, and rapid feedback loops.

• Data analysis and insights are driven by the needs of intelligence operations, with a focus on actionable intelligence and mission outcomes.

• Workflow planning and optimization strategies are critical for developing efficient and effective software tools and data pipelines.

• Automation and efficiency practices are key, particularly through CI/CD pipelines and automated testing.

Company Website: https://www.invictusic.com/

📝 Enhancement Note: The company operates within a highly sensitive and regulated sector (intelligence community). This implies a culture that prioritizes security, discretion, accuracy, and adherence to strict protocols. Collaboration is crucial, but it occurs within a framework of established government contracting processes and security requirements.

📈 Career & Growth Analysis

Operations Career Level: This role is positioned as a mid-level Data Engineer/Software Prototyper. It requires independent contribution to technical development, problem-solving, and collaboration within a team. The role is instrumental in translating complex requirements into tangible software solutions, indicating a significant level of responsibility and technical autonomy.

Reporting Structure: The Data Engineer will report to a technical lead or project manager and will collaborate closely with Data Management Support Officers, Data Scientists, and the ISSE. This structure indicates a project-driven environment where cross-functional teamwork is essential for success.

Operations Impact: The Data Engineer's work directly impacts the effectiveness and efficiency of intelligence operations. By developing critical software prototypes, data management tools, and AI/ML integrations, they contribute to enhanced intelligence gathering, analysis, and dissemination capabilities, ultimately supporting national security missions.

Growth Opportunities:

• Technical Specialization: Deepen expertise in specific programming languages, cloud platforms, AI/ML techniques, or cybersecurity for intelligence systems.

• Leadership Potential: Advance into technical lead or project management roles, overseeing development teams and project lifecycles.

• Advanced Clearance Levels: Progress to roles requiring higher-level security clearances or specialized polygraphs.

• Cross-Functional Expertise: Gain broader experience in areas like cybersecurity, data science, or systems engineering through collaboration and project involvement.

• Domain Expertise: Develop specialized knowledge within specific intelligence disciplines (e.g., CI/HUMINT).

📝 Enhancement Note: Growth in this sector is often tied to demonstrated technical proficiency, successful project delivery, and maintaining the required security clearances. The company's affiliation with Red River may also offer pathways into larger, more diverse projects or specialized business units within the parent organization.

🌐 Work Environment

Office Type: The role is on-site in Reston, VA. This typically means working within a secure government contractor facility or a designated office space that adheres to strict security protocols required for handling classified information and working on sensitive projects.

Office Location(s): Reston, VA. This location is a hub for government contracting and technology companies, offering access to a skilled workforce and proximity to government agencies.

Workspace Context:

• The workspace will be secure, adhering to TS/SCI requirements, which may involve controlled access, specific IT security policies, and potentially limited personal electronic devices.

• Collaboration will be facilitated through secure communication channels and in-person meetings within designated areas.

• Access to advanced computing resources, development tools, and potentially specialized hardware or software environments will be provided.

• The environment encourages close teamwork and direct interaction with colleagues from various technical disciplines.

Work Schedule: The standard work schedule is 40 hours per week, with potential for overtime as dictated by project needs. While the role is on-site, there might be some flexibility in daily start/end times, but the core requirement is physical presence.

📝 Enhancement Note: The on-site requirement and the TS/SCI clearance are critical aspects of the work environment. Candidates must be comfortable operating within highly secure and regulated settings, where access and data handling are strictly controlled.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: HR or recruiter will review applications for minimum qualifications, including experience and clearance status.

• Technical Interview: Expect in-depth technical questions covering programming languages, data engineering concepts, software development methodologies, API design, cloud computing, and AI/ML integration. Be prepared to discuss specific projects and challenges.

• Security & Clearance Verification: Detailed background checks and verification of security clearance status will be conducted.

• Team/Hiring Manager Interview: Discussion focused on team fit, problem-solving approach, collaboration style, and understanding of the intelligence community's unique requirements.

• Potential Technical Assessment/Coding Challenge: A practical exercise or coding challenge may be administered to evaluate real-time problem-solving and coding skills.

Portfolio Review Tips:

• Focus on Relevance: Curate projects that demonstrate experience with data ingestion, API development, software prototyping, cloud deployment, and secure development practices.

• Quantify Impact: Whenever possible, use metrics to highlight the improvements or efficiencies your work brought (e.g., reduced processing time, increased data accuracy, successful system integration).

• Highlight Security: If showcasing projects from sensitive environments, focus on the methodologies used (e.g., secure coding practices, adherence to protocols) rather than sensitive data details.

• Structure Clearly: Organize your portfolio logically, perhaps by skill area or project type, with concise descriptions for each item.

• Prepare to Discuss: Be ready to walk through 1-2 key projects in detail, explaining your role, the challenges, your solutions, and the outcomes.

Challenge Preparation:

• Coding Practice: Refresh skills in Python, Java, or other relevant languages. Practice common data structures and algorithms.

• System Design: Prepare to discuss how you would design a data pipeline or a prototype tool given specific requirements, considering scalability, security, and performance.

• API Design: Review RESTful API principles and common design patterns.

• Cloud Concepts: Be ready to discuss basic cloud computing concepts and deployment strategies.

• Intelligence Context: Understand the general challenges and requirements of working within the intelligence community (security, data sensitivity, mission criticality).

📝 Enhancement Note: The interview process will heavily scrutinize both technical competence and the ability to operate within a secure, mission-critical environment. A strong portfolio that demonstrates practical application of skills, particularly in areas related to data integration and software prototyping for sensitive applications, will be crucial.

🛠 Tools & Technology Stack

Primary Tools:

• Programming Languages: Python (highly probable for data engineering and scripting), Java, C++, Go.

• Cloud Platforms: AWS, Azure, GCP, or specific government cloud environments (e.g., AWS GovCloud, Azure Government).

• API Development: Frameworks like Flask/Django (Python), Spring (Java), Node.js. Tools for API documentation (e.g., Swagger/OpenAPI).

• Containerization: Docker, Kubernetes (for deployment and orchestration).

• Version Control: Git (e.g., GitHub, GitLab, Bitbucket).

Analytics & Reporting:

• Data Processing: Apache Spark, Hadoop ecosystem (if applicable).

• Database Technologies: SQL databases (PostgreSQL, MySQL), NoSQL databases (e.g., MongoDB, Cassandra) depending on data needs.

• Visualization Tools: Tableau, Power BI, or custom dashboarding solutions if required for prototypes.

CRM & Automation:

• CI/CD Tools: Jenkins, GitLab CI, GitHub Actions, Azure DevOps.

• Automated Testing Frameworks: Pytest, JUnit, Selenium, etc.

• Messaging Queues: Kafka, RabbitMQ (for data pipelines).

📝 Enhancement Note: The stack is likely to be modern and cloud-centric, with a strong emphasis on languages and tools suitable for building robust, scalable, and secure applications. Proficiency in Python is almost a given for this type of role. Given the intelligence context, familiarity with secure development practices and tools that support compliance is also important.

👥 Team Culture & Values

Operations Values:

• Mission Focus: A strong dedication to supporting national security missions and delivering impactful solutions for intelligence operations.

• Security First: An unwavering commitment to data security, confidentiality, and adherence to all relevant protocols and regulations.

• Technical Excellence: A drive for high-quality, robust, and efficient software development and data engineering practices.

• Collaboration & Teamwork: Valuing open communication, mutual support, and shared problem-solving among team members.

• Innovation & Adaptability: Embracing new technologies and methodologies to develop cutting-edge solutions and adapt to evolving operational needs.

• Integrity & Professionalism: Maintaining the highest ethical standards and professional conduct in all aspects of work.

Collaboration Style:

• Cross-functional Integration: Close collaboration with Data Scientists, ISSEs, Data Management Officers, and Project Managers to ensure seamless integration of software prototypes and data capabilities.

• Process Review Culture: Openness to constructive feedback during code reviews and design discussions to collectively improve solutions.

• Knowledge Sharing: Encouraging the sharing of technical expertise, best practices, and lessons learned to foster team growth and collective problem-solving.

• Agile Approach: Working in iterative cycles, with frequent communication and feedback loops to ensure alignment and rapid iteration.

📝 Enhancement Note: The culture will be heavily influenced by the government contracting and intelligence sector. Expect a professional, disciplined, and security-conscious environment where teamwork is essential but operates within defined protocols and a strong sense of mission purpose.

⚡ Challenges & Growth Opportunities

Challenges:

• Navigating Secure Environments: Adapting to strict security protocols, clearance requirements, and potential limitations on tools or data access inherent in intelligence work.

• Translating Requirements: Accurately interpreting and translating complex, often ambiguous, operational requirements from non-technical stakeholders into functional software.

• Integration Complexity: Ensuring seamless interoperability between disparate systems and data sources within a potentially heterogeneous intelligence community IT landscape.

• Rapid Prototyping Demands: Balancing the need for rapid development and iteration with the stringent quality and security standards required for intelligence applications.

• Staying Current: Keeping pace with rapidly evolving technologies in data engineering, AI/ML, and software development while working within secure, sometimes constrained, environments.

Learning & Development Opportunities:

• Advanced Skill Development: Opportunities to gain deeper expertise in AI/ML frameworks, advanced cloud architecture, secure coding practices, and big data technologies.

• Industry Certifications: Support for obtaining relevant certifications in cloud computing, cybersecurity, or specific programming languages.

• Mentorship: Access to experienced engineers and subject matter experts within Invictus IC and Red River for guidance and knowledge transfer.

• Exposure to Cutting-Edge Tech: Working with novel technologies and prototypes that push the boundaries of intelligence analysis and operations.

• Career Progression: Pathways to senior engineering roles, technical leadership, or specialization in niche areas within national security technology.

📝 Enhancement Note: The challenges are typical of working in a high-stakes, secure environment, requiring both technical acumen and strong adaptability. The growth opportunities are substantial for those who excel technically and can navigate the specific demands of the intelligence sector.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you had to translate a complex, ambiguous requirement into a functional software prototype. What was your process, and what were the key challenges?" (Focus on requirements gathering, iterative design, and stakeholder communication.)

• "How would you design a data ingestion pipeline for diverse intelligence data sources, considering security, scalability, and real-time processing needs?" (Prepare to discuss ETL/ELT, data formats, error handling, and security measures.)

• "Walk us through your experience with API design and implementation. What principles do you follow, and how do you ensure security and performance?" (Be ready to discuss REST, GraphQL, authentication, authorization, and documentation.)

• "Discuss a project where you integrated AI/ML algorithms into a software application. What was your role, what challenges did you face, and how did you overcome them?" (Highlight collaboration with data scientists and the technical integration process.) Company & Culture Questions:

• "What interests you about working for Invictus International Consulting and supporting national security missions?" (Research the company's mission and values, and articulate your alignment.)

• "How do you approach working in a highly secure environment with strict protocols?" (Emphasize your understanding of security importance and your ability to adapt.)

• "Describe your experience working in cross-functional teams. How do you ensure effective collaboration with individuals from different technical backgrounds?" (Focus on communication, problem-solving, and shared goals.) Portfolio Presentation Strategy:

• Select 1-2 Key Projects: Choose projects that best showcase your skills in data ingestion, API development, software prototyping, and secure development.

• Structure Your Narrative: For each project, clearly outline:

  • The Problem/Operational Need
  • Your Role and Responsibilities
  • The Technical Solution (mentioning specific tools, languages, and approaches)
  • Key Challenges and How You Overcame Them
  • The Outcome/Impact (quantify if possible)

• Highlight Security Aspects: Emphasize how you incorporated security considerations throughout the development lifecycle.

• Be Ready for Deep Dives: Anticipate questions about specific technical decisions, trade-offs made, and alternative approaches considered.

📝 Enhancement Note: Preparation should focus on demonstrating practical problem-solving skills, technical depth, and a clear understanding of the security and mission-critical nature of the work. Your portfolio is your primary tool for showcasing these capabilities.

📌 Application Steps

To apply for this Data Engineer - Software Prototyping position:

• Submit your application through the provided link on Invictus International Consulting's applicant portal.

• Tailor Your Resume: Emphasize your experience with software prototyping, data engineering, API development, cloud platforms, and any relevant security clearance (TS/SCI). Use keywords from the job description.

• Prepare Your Portfolio: Curate a selection of projects that best highlight your skills in data ingestion, API design, software development, and cloud deployment. Be ready to discuss these in detail.

• Research Invictus IC & Red River: Understand their mission, values, and the types of projects they undertake within the government and national security sectors.

• Practice Technical Questions: Review common interview questions for Data Engineers and Software Engineers, focusing on your specific technologies and experience. Be prepared to discuss your problem-solving approach.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.