Required Qualifications: • Bachelor’s degree in computer science, Data Science, Information Systems, Mathematics, Statistics, Engineering, or a closely related field • 5-7 years of progressive, hands-on experience in data analytics, data engineering, or a closely related discipline • Demonstrated experience delivering data solutions in support of government, defense, or large-scale enterprise programs • SQL & Databases: Strong command of SQL and experience with relational databases (e.g., PostgreSQL, Microsoft SQL Server) • ETL / ELT Pipelines: Hands-on experience designing and implementing data pipelines using tools such as Apache Airflow, Informatica, Talend, dbt, or equivalent • Cloud Platforms: Experience with AWS, Microsoft Azure, including managed data services (Azure Synapse, BigQuery) • BI & Visualization: Proficiency with Power BI, Alteryx, or equivalent business intelligence tools • Data Warehousing: Familiarity with data warehousing concepts, dimensional modeling, and data lake architecture (ADLS, ADF) • Must be a US citizen willing to obtain and maintain a TS/SCI security clearance Desired Qualifications: • Experience navigating shared infrastructure models — consuming centrally managed data platforms without owning the underlying infrastructure • Prior experience working with or alongside a CIO office or enterprise IT governance function in a consumer/integrator capacity • Knowledge of NIST AI Risk Management Framework (AI RMF) and its data-related implications • Relevant certifications: Microsoft Certified: Azure Data Engineer Associate, dbt Certified Developer, CDMP (Certified Data Management Professional), or equivalent • Active TS/SCI security clearance Peraton is seeking a skilled and motivated Lead Data & AI Analyst / Engineer to join our organization to support Peraton corporate data and AI knowledge strategy. You will serve as a technical lead and subject matter expert, collaborating closely with corporate stakeholders, data architects, and cross-functional teams to deliver high-quality, secure, and data and knowledge products that further Peraton corporate growth and business acquisition processes. This mid-level role is responsible for planning, coordinating, and managing the AI data foundation that powers Peraton's AI adoption initiatives — ensuring that the right data is available, governed, trusted, and accessible for the right analytical and AI-driven purposes. Key Responsibilities: Data Planning & Architecture • Define, document and maintain the AI and data requirements and quality standards for Corporate Growth & Business Operations — both structured and unstructured data • Define and document data domain models, entity relationships, and data flow diagrams across source systems (CRM, ERP, HRIS, proposal repositories, contract vehicles) • Work within the CIO-managed data catalog to ensure Growth & Business Operations data assets are properly inventoried, normalized, classified, tagged by domain and sensitivity, and discoverable by authorized AI consumers • Participate in enterprise data governance forums and represent the AI and data requirements, priorities on CIO managed data assets. • Partner with the CIO office to define and enforce data quality standards — including completeness, accuracy, timeliness, and consistency scoring — for data assets feeding AI workflows Data Integration, Engineering & Pipeline Development • Develop and manage AI-specific data pipelines to CIO managed lakehouse/warehouse environments • Collaborate with IRAD engineers to integrate data pipelines into the broader AI platform infrastructure • Coordinate with the CIO office to define data access patterns, API contracts, and export/query interfaces that allow AI workloads to consume enterprise data efficiently and securely • Implement data versioning and lineage tracking at the AI consumption layer to ensure full traceability from CIO-managed source to AI-generated output