Data & AI Integration Engineer - Mid-Level

Welcome page Returning candidate? Log back in! Data & AI Integration Engineer - Mid-Level Job Locations US-VA-Reston | US-NJ-Basking Ridge | US-FL-Melbourne Requisition ID 2026-166005 Position Category Information Technology Clearance Top Secret/SCI Responsibilities 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 dataDefine 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 consumersParticipate 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 workflowsData Integration, Engineering & Pipeline DevelopmentDevelop and manage AI-specific data pipelines to CIO managed lakehouse/warehouse environmentsCollaborate with IRAD engineers to integrate data pipelines into the broader AI platform infrastructureCoordinate 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 securelyImplement data versioning and lineage tracking at the AI consumption layer to ensure full traceability from CIO-managed source to AI-generated output Qualifications Required Qualifications:Bachelor’s degree in computer science, Data Science, Information Systems, Mathematics, Statistics, Engineering, or a closely related field5-7 years of progressive, hands-on experience in data analytics, data engineering, or a closely related disciplineDemonstrated experience delivering data solutions in support of government, defense, or large-scale enterprise programsSQL & 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 equivalentCloud Platforms: Experience with AWS, Microsoft Azure, including managed data services (Azure Synapse, BigQuery)BI & Visualization: Proficiency with Power BI, Alteryx, or equivalent business intelligence toolsData 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 clearanceDesired Qualifications:Experience navigating shared infrastructure models — consuming centrally managed data platforms without owning the underlying infrastructurePrior experience working with or alongside a CIO office or enterprise IT governance function in a consumer/integrator capacityKnowledge of NIST AI Risk Management Framework (AI RMF) and its data-related implicationsRelevant...