Senior Principal, Chief of Data Tradecraft

Maximusis currently seeking aSenior Principal, Chief of Data Tradecraft The Senior Principal, Chief of Data Tradecraft is the enterprise authority for the methods, standards, patterns, and practices used to transform data into actionable insight, sound decisions, mission outcomes, and responsible AI-enabled capabilities. The role combines technical depth, analytical rigor, product thinking, federal mission awareness, and executive communication to improve the quality, repeatability, and impact of data and AI solutions across the organization. This is a senior individual contributor role. The Chief of Data Tradecraft leads through expertise, influence, facilitation, and mentorship rather than formal people management. The role works across Data Management & Analytics, technology, operations, business segments, and client-facing teams to develop reusable tradecraft, shape high-value data products, guide AI-enabled analytical approaches, and translate complex architectures into practical business and mission outcomes. This is a remote position. Essential Duties and Responsibilities: Own Tier 3 (Data Management) and Tier 4 (Solution Foundation): Lead ontology development and extension (including AIModel and Identity entities), metadata standards, data‑quality management (target>99%), integration pipelines, and lifecycle policies. Lead the design and implementation of the enterprise data architecture, including the Azure Data Lakehouse, Purview governance layer, Synapse analytics environment, Data Factory pipelines, and machine‑learning workspaces. Drive ontology enforcement through JSON Schema + Pydantic validation, TDFPolicy axioms, and DataGuard prototypes (RBAC/ABAC, OpenTDF). Build and scale AI-readiness capabilities, including RAG-ready datasets, vector stores, ethical model governance, bias checks, and AIModel tracking. Lead technical pilots and segment rollouts (e.g., CDL as first GLDE node, Federal Services ontology pilot). Ensure zero-trust compliance, data residency, and audit-ready lineage standers across all assets. Partner closely with the parallel Sr Director - Data Strategy and Governance to make policies technically enforceable. Deliver measurable outcomes such as 99% data quality, 100% ontology conformance, scalable KBQ automation, and foundation for 10-15% revenue uplift / 15-25% cost reduction. Job-Specific Essential Duties and Responsibilities: Role Purpose: Define and institutionalize enterprise data and analytical tradecraft. Advance decision intelligence and responsible AI-enabled analytical practices. Establish repeatable methods for governed data products, evidence, and insight delivery. Improve analytical quality, trust, explainability, and adoption across business and mission contexts. Create practical playbooks, patterns, demonstrations, and accelerators that move concepts from pilot to scale. Mentor practitioners and convene communities of practice without direct-report responsibility. Enterprise Data Tradecraft: Establish enterprise standards for analytical rigor, evidence quality, reproducibility, and decision support. Develop reusable analytical playbooks, reference patterns, operating models, and assessment methods. Define what good looks like for insight generation, analytical products, and data-informed decisions. Identify recurring delivery challenges and codify practical methods that improve quality and speed. AI-Enabled Analytics and Decision Intelligence: Shape methods for applying generative AI, retrieval-augmented generation, agentic AI, and knowledge graphs within governed analytical workflows. Develop evaluation approaches for AI quality, data readiness, traceability, human oversight, and mission fitness. Guide responsible adoption of emerging AI capabilities in regulated and high-consequence environments. Prototype and demonstrate AI-enabled approaches that clarify value, limitations, risks, and pathways to scale. Data Product Strategy and Architecture: Define practical standards for domain-oriented, governed, reusable, and discoverable data products. Advise teams on product vision, use-case prioritization, roadmap development, and adoption measures. Connect business and mission requirements to data architecture, cloud analytics, and platform capabilities. Promote data-as-code, product lifecycle, observability, and quality patterns that support reliable reuse. Semantic and Knowledge Enablement: Advance the use of ontology, semantic models, metadata, and knowledge graphs to improve context and analytical consistency. Connect business concepts, authoritative data, analytical logic, and decision outcomes. Partner with architecture and governance teams to make enterprise meaning operational and consumable. Executive and Client Advisory: Serve as a trusted advisor to executives, program leaders, architects, product teams, and federal mission stakeholders. Translate complex data and AI concepts into clear decisions, roadmaps, briefings, demonstrations, and written thought leadership. Facilitate workshops that align stakeholders on mission needs, analytical opportunities, technical options, and adoption paths. Support strategic pursuits and solution shaping where advanced data, analytics, or AI tradecraft is differentiating. Practice Development and Mentorship: Mentor analysts, data scientists, architects, engineers, and product leaders through coaching, design reviews, and working sessions. Lead a community of practice that shares methods, lessons learned, exemplars, and reusable assets. Create training, field guides, white papers, and reference implementations that raise enterprise capability. Priority Outcomes: An enterprise tradecraft framework covering analytical methods, evidence standards, quality controls, decision support, and AI-assisted analysis. A portfolio of playbooks, reference architectures, repeatable demonstrations, and accelerators that teams can apply across domains. A practical methodology for defining, governing, delivering, measuring, and improving enterprise data products. Repeatable evaluation and governance approaches for AI-enabled analytical solutions in regulated environments. Methods connecting ontology, knowledge graphs, metadata, and authoritative data to analytical and AI use cases. A visible community of practice and mentoring model that improves analytical capability across the enterprise. Clear, evidence-based guidance that helps executives make informed investment and adoption decisions. Minimum Requirements '- Bachelor's degree in relevant field of study. 12+ years of relevant professional experience required. Familiarity with DoD, IC, and Federal missions, functions, tasks, and systems environments required. Job-Specific Minimum Requirements: Additional years of relevant experience will be considered in lieu of degree. Extensive experience delivering complex data, analytics, AI, digital modernization, or mission technology initiatives. Demonstrated ability to translate business or mission needs into deployable data and analytical capabilities. Deep experience advising senior executives and technical leaders on data, AI, architecture, product strategy, and modernization. Experience working in regulated, security-sensitive, healthcare, defense, intelligence, or federal civilian environments. Demonstrated success developing methods, frameworks, governance approaches, reference architectures, or reusable solution patterns. Experience influencing cross-functional teams and leading through technical credibility rather than organizational authority. Core Competencies: Strategic systems thinking. Technical depth across data, analytics, AI, cloud, architecture, and product disciplines. Analytical rigor and evidence-based decision making. Data product and user-outcome orientation. Executive communication and data storytelling. Workshop facilitation, teaching, and mentorship. Innovation balanced with security, governance, ethics, and operational reality. Influence without formal authority. Measures of Success: Adoption of tradecraft standards, playbooks, and reusable patterns across multiple teams or business domains. Improved clarity, quality, explainability, and repeatability of analytical and AI-enabled solutions. Acceleration of priority data and AI use cases from concept through demonstration, delivery, and scale. Increased reuse and measurable business or mission value from governed data products. Growth in practitioner capability through mentoring, communities of practice, and applied learning. Executive and client confidence in the organization’s data, analytics, and AI methods and recommendations. Role Characteristics: Enterprise scope with significant autonomy and visibility. No standing people-management responsibility; may lead virtual teams, working groups, pilots, and communities of practice. Works across internal strategy, delivery, innovation, and selected client-facing contexts. Requires comfort operating amid ambiguity, shaping new practices, and moving between detailed technical work and senior-level communication. May require travel and participation in secure or regulated customer environments based on assignment. Preferred Skills and Qualifications Advanced degree in systems engineering, computer science, analytics, or a related discipline. Experience with cloud data and analytics platforms such as Databricks, Snowflake, Elasticsearch, or comparable technologies. Hands-on fluency with Python, SQL, APIs, data modeling, visualization, and modern AI and machine-learning solution patterns. Experience with generative AI, retrieval-augmented generation, LLM orchestration, agentic AI, knowledge graphs, or semantic technologies. Experience establishing data quality, observability, responsible AI, or model evaluation practices. Product strategy, roadmapping, market positioning, solution shaping, or go-to-market experience. Experience delivering secure solutions under FedRAMP, RMF, ATO, HIPAA-aligned, or comparable control environments. Active security clearance or eligibility to obtain one, where required by assignment. The organization is committed to a workplace grounded in fairness, respect, accessibility, and equal opportunity. Employment decisions are based on role requirements, qualifications, and business needs, consistent with applicable law and company policy. Reasonable accommodations are available for qualified individuals with disabilities. #techjobs #veteranspage #LI-Remote Maximus is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, age, national origin, disability, veteran status, genetic information and other legally protected characteristics. Minimum Salary $207,400 Maximum Salary $306,600 #J-18808-Ljbffr Maximus