Systems Planning & Analysis
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Overview
Systems Planning and Analysis, Inc. (SPA) delivers high-impact technical solutions to complex national security issues. With over 50 years of business expertise and consistent growth, we are known for continuous innovation for our government customers, both in the US and abroad. Our exceptionally talented team is highly collaborative in spirit and practice, producing Results that Matter. Come work with the best! We offer opportunities, unique challenges, and clear-sighted commitment to the mission. SPA: Objective. Responsive. Trusted.
SPA has established a Fellows program in which there are positions aligned to Capabilities and Domains in support of the entire SPA company across all Divisions. The Data Engineering Fellow serves as the corporate lead responsible for providing strategic leadership, guidance, and experienced mentoring across SPA in technology and innovation related to Data-driven Engineering, Analytics, and Architectures in support of present and future systems. SPA remains a forefront leader in delivering cutting-edge analytics, modeling & simulation solutions, wargaming, and resilient accurate integrated engineering solutions to clients across the Federal Government. At the core of all this capability is the underlying data architecture, tools, and capabilities.
The Data Engineering Fellow reports into the Chief Capabilities Office (CCO) and will help SPA design and mature robust data architectures and analytic approaches that leverage a wide range of data types (e.g., structured/tabular, log data, text, imagery, video, sensor/telemetry) to deliver actionable insights for government customers. The focus is on turning structured and unstructured, distributed data into reliable, secure, and usable information to support the customer mission.
This is a fractional, part-time role expected to average approximately 40 hours per quarter (roughly one week of full-time effort every three months), focused on high-impact strategic contributions rather than day-to-day operations. Contributions will advance the Capability expertise broadly across the many Domains SPA supports.
Cultivation of market-relevant SPA expertise in data engineering and analytics:
Define expert knowledge and skills across Beginner, Intermediate, and Advanced levels, focusing on current market needs and future anticipation through inciteful industry knowledge and engagement. Sustain structured repositories including white papers, case studies, and pedigreed data sets to facilitate expertise development and collaboration. Implement quality assurance within training, products, and development processes related to data engineering. Define an expertise assessment process leading to tiered certifications for the Capability. Create objective, appropriate, and transparent assessment methods to certify expertise levels for Data Engineers, Data Analyst, and Data Architects at SPA. Leverage external certifications and qualifications for assisting SPA in playing and executing credible training in areas of Data Engineering and Analytics.
Ensure the conduct of high-quality training at all expert levels. Promote best practices, emerging techniques, and professional development. Provide high-quality training across data engineering disciplines through community of practice, training, and various levels of engagement. Work across SPA to assure accessible training and information for data engineers across SPA.. Encourage personal expertise growth, focusing on mentoring young, mid-level and more experienced personnel.
Ensure SPA expertise representation is evident across market/client platforms, conferences, and social media as beneficial to the business.
Participate in strategy sessions for data-driven solutions on high-priority opportunities. Support proposal development by contributing insights or identifying expertise partners.
Train the team in client engagement, professional presentations, and writing—highlighting responsible handling of classified information. Support customer meetings and engagements as appropriate to assisting the capture and BD process.
Lead forward-looking initiatives that support innovation & influence, stay ahead of market trends and prevent client surprises while contextualizing innovation historically. Advocate for new areas of expertise to fulfill client needs and position SPA as an industry thought leader, with particular emphasis on the following areas
Strategic data and analytics guidance: Provide periodic strategic guidance on SPA’s enterprise data engineering and analytics strategy, ensuring alignment with government customer mission requirements and federal priorities such as national security, mission efficiency, and responsible data use.
Architecture and technical review: Review and advise on the design of data platforms and pipelines (e.g., data lakes, warehouses, streaming architecture) that ingest, transform, and curate diverse data types at varying scales and security levels. Participate in targeted design reviews and technical deep dives rather than continuous implementation.
Data governance and best practices: Advise on data modeling, data quality, data storage, data lakes, data access controls, and data governance frameworks, including alignment with federal data policies. Help define reference architectures, standards, and patterns; validate that proposed solutions are accurate, reproducible, and mission aligned.
Advanced data engineering, analytics, and predictive modeling: Provide expert input on the curation, ingest, normalization, and labeling of data for statistical models, forecasting approaches, anomaly detection methods, and machine learning solutions for mission problems (e.g., force readiness, intelligence analysis, logistics optimization, operational risk). Focus on mission-specific data sources, formats, and platform integration requirements.
Visualization and decision support: Advise on the design principles and overall approach for dashboards, geospatial products, and interactive visualizations that support senior decision-makers. Review and critique key artifacts rather than building them directly.
Data Engineering Support for Artificial Intelligence: Advance SPA’s capability development by assisting the Applied AI Fellow in incorporating data engineering best practices into emerging Artificial Intelligence (AI) methods and architectures. Guide the curation, ingest, formatting, and labeling of data to support AI enablement, including machine learning and automation approaches to strengthen analytic rigor, improve model performance, and enhance enterprise‑wide decision‑support solutions.
Active DoD Secret clearance with ability to obtain and maintain a Top Secret clearance
Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Information Systems, Engineering, Mathematics, or a related technical discipline
15+ years of progressively responsible experience in data engineering, enterprise data architecture, analytics, or related technical leadership roles
Demonstrated national-level technical leadership and recognition as a subject matter expert in data engineering, enterprise data architecture, or advanced analytics, evidenced by significant technical contributions, publications, invited speaking engagements, leadership of major government initiatives, patents, or comparable accomplishments
Demonstrated expertise designing, evaluating, and advising on enterprise-scale data architectures supporting structured, semi-structured, and unstructured data across complex mission environments
Extensive experience with data platforms, data lakes, data warehouses, ETL/ELT pipelines, streaming architectures, cloud-native data ecosystems, and modern data integration practices
Experience supporting U.S. Government, Department of Defense, Intelligence Community, or other federal customers
Deep understanding of data governance, metadata management, data quality, master data management, data security, and federal data standards and policies
Demonstrated experience enabling advanced analytics, artificial intelligence, machine learning, and predictive analytics through scalable data engineering practices
Proven ability to provide strategic technical guidance to executive leadership, chief engineers, program managers, and multi-disciplinary engineering teams
Demonstrated experience mentoring technical professionals, developing communities of practice, and building organizational capability through training and knowledge sharing
Excellent written and verbal communication skills, including experience authoring technical white papers, strategy documents, executive briefings, and proposal content
Desired Qualifications
Master's or Ph.D. in Computer Science, Data Science, Artificial Intelligence, Engineering, Applied Mathematics, or a related technical discipline
Active Top Secret/SCI security clearance
Experience architecting secure cloud-based data solutions within AWS, Microsoft Azure, Google Cloud, GovCloud, or classified cloud environments
Expertise with modern data engineering platforms and technologies such as Databricks, Snowflake, Apache Spark, Kafka, Airflow, dbt, Delta Lake, or comparable technologies
Experience supporting national security missions involving defense, intelligence, cyber, space, homeland security, or related domains
Familiarity with the DoD Digital Engineering Strategy, DoD Data Strategy, CJADC2, Digital Twins, Model-Based Systems Engineering (MBSE), or related digital transformation initiatives
Experience establishing enterprise data governance frameworks, reference architectures, technical standards, and best practices
Relevant professional certifications (e.g., AWS Certified Data Engineer, Microsoft Azure Data Engineer Associate, Google Professional Data Engineer, Databricks Certified Data Engineer, Snowflake SnowPro, DAMA CDMP, TOGAF)
Established professional relationships across government, industry, academia, and professional organizations that enhance SPA's visibility and technical leadership
At SPA, we strive to deliver a robust total compensation package that will attract and retain top talent. Elements of the compensation package include competitive base pay and variable compensation opportunities. SPA provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health insurance, flexible spending accounts, health savings accounts, retirement savings plans, life and disability insurance programs, and a number of programs that provide both paid and unpaid time away from work. The specific programs and options available to any given employee may vary depending on eligibility factors such as geographic location, date of hire, etc. Please note that the salary information shown below is a general guideline only. Salaries are commensurate with experience and qualifications, as well as market and business considerations. Pay Transparency Range: 175k - 265k
At SPA, we strive to deliver a robust total compensation package that will attract and retain top talent. Elements of the compensation package include competitive base pay and variable compensation opportunities. SPA provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health insurance, flexible spending accounts, health savings accounts, retirement savings plans, life and disability insurance programs, and a number of programs that provide for both paid and unpaid time away from work. The specific programs and options available to any given employee may vary depending on eligibility factors such as geographic location, date of hire, etc. Please note that the salary information shown below is a general guideline only. Salaries are commensurate with experience and qualifications, as well as market and business considerations. Virginia, Pay Transparency Salary range: USD $175,000.00/Yr. - USD $265,000.00/Yr.
The Data Engineering Fellow reports into the Chief Capabilities Office (CCO) and will help SPA design and mature robust data architectures and analytic approaches that leverage a wide range of data types (e.g., structured/tabular, log data, text, imagery, video, sensor/telemetry) to deliver actionable insights for government customers. The focus is on turning structured and unstructured, distributed data into reliable, secure, and usable information to support the customer mission.
This is a fractional, part-time role expected to average approximately 40 hours per quarter (roughly one week of full-time effort every three months), focused on high-impact strategic contributions rather than day-to-day operations. Contributions will advance the Capability expertise broadly across the many Domains SPA supports.
Cultivation of market-relevant SPA expertise in data engineering and analytics:
Define expert knowledge and skills across Beginner, Intermediate, and Advanced levels, focusing on current market needs and future anticipation through inciteful industry knowledge and engagement. Sustain structured repositories including white papers, case studies, and pedigreed data sets to facilitate expertise development and collaboration. Implement quality assurance within training, products, and development processes related to data engineering. Define an expertise assessment process leading to tiered certifications for the Capability. Create objective, appropriate, and transparent assessment methods to certify expertise levels for Data Engineers, Data Analyst, and Data Architects at SPA. Leverage external certifications and qualifications for assisting SPA in playing and executing credible training in areas of Data Engineering and Analytics.
Ensure the conduct of high-quality training at all expert levels. Promote best practices, emerging techniques, and professional development. Provide high-quality training across data engineering disciplines through community of practice, training, and various levels of engagement. Work across SPA to assure accessible training and information for data engineers across SPA.. Encourage personal expertise growth, focusing on mentoring young, mid-level and more experienced personnel.
Ensure SPA expertise representation is evident across market/client platforms, conferences, and social media as beneficial to the business.
Participate in strategy sessions for data-driven solutions on high-priority opportunities. Support proposal development by contributing insights or identifying expertise partners.
Train the team in client engagement, professional presentations, and writing—highlighting responsible handling of classified information. Support customer meetings and engagements as appropriate to assisting the capture and BD process.
Lead forward-looking initiatives that support innovation & influence, stay ahead of market trends and prevent client surprises while contextualizing innovation historically. Advocate for new areas of expertise to fulfill client needs and position SPA as an industry thought leader, with particular emphasis on the following areas
Strategic data and analytics guidance: Provide periodic strategic guidance on SPA’s enterprise data engineering and analytics strategy, ensuring alignment with government customer mission requirements and federal priorities such as national security, mission efficiency, and responsible data use.
Architecture and technical review: Review and advise on the design of data platforms and pipelines (e.g., data lakes, warehouses, streaming architecture) that ingest, transform, and curate diverse data types at varying scales and security levels. Participate in targeted design reviews and technical deep dives rather than continuous implementation.
Data governance and best practices: Advise on data modeling, data quality, data storage, data lakes, data access controls, and data governance frameworks, including alignment with federal data policies. Help define reference architectures, standards, and patterns; validate that proposed solutions are accurate, reproducible, and mission aligned.
Advanced data engineering, analytics, and predictive modeling: Provide expert input on the curation, ingest, normalization, and labeling of data for statistical models, forecasting approaches, anomaly detection methods, and machine learning solutions for mission problems (e.g., force readiness, intelligence analysis, logistics optimization, operational risk). Focus on mission-specific data sources, formats, and platform integration requirements.
Visualization and decision support: Advise on the design principles and overall approach for dashboards, geospatial products, and interactive visualizations that support senior decision-makers. Review and critique key artifacts rather than building them directly.
Data Engineering Support for Artificial Intelligence: Advance SPA’s capability development by assisting the Applied AI Fellow in incorporating data engineering best practices into emerging Artificial Intelligence (AI) methods and architectures. Guide the curation, ingest, formatting, and labeling of data to support AI enablement, including machine learning and automation approaches to strengthen analytic rigor, improve model performance, and enhance enterprise‑wide decision‑support solutions.
Active DoD Secret clearance with ability to obtain and maintain a Top Secret clearance
Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Information Systems, Engineering, Mathematics, or a related technical discipline
15+ years of progressively responsible experience in data engineering, enterprise data architecture, analytics, or related technical leadership roles
Demonstrated national-level technical leadership and recognition as a subject matter expert in data engineering, enterprise data architecture, or advanced analytics, evidenced by significant technical contributions, publications, invited speaking engagements, leadership of major government initiatives, patents, or comparable accomplishments
Demonstrated expertise designing, evaluating, and advising on enterprise-scale data architectures supporting structured, semi-structured, and unstructured data across complex mission environments
Extensive experience with data platforms, data lakes, data warehouses, ETL/ELT pipelines, streaming architectures, cloud-native data ecosystems, and modern data integration practices
Experience supporting U.S. Government, Department of Defense, Intelligence Community, or other federal customers
Deep understanding of data governance, metadata management, data quality, master data management, data security, and federal data standards and policies
Demonstrated experience enabling advanced analytics, artificial intelligence, machine learning, and predictive analytics through scalable data engineering practices
Proven ability to provide strategic technical guidance to executive leadership, chief engineers, program managers, and multi-disciplinary engineering teams
Demonstrated experience mentoring technical professionals, developing communities of practice, and building organizational capability through training and knowledge sharing
Excellent written and verbal communication skills, including experience authoring technical white papers, strategy documents, executive briefings, and proposal content
Desired Qualifications
Master's or Ph.D. in Computer Science, Data Science, Artificial Intelligence, Engineering, Applied Mathematics, or a related technical discipline
Active Top Secret/SCI security clearance
Experience architecting secure cloud-based data solutions within AW
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