Principal Data Engineer

Leidos has an exciting opportunity for a Data Engineer in our Intel Sector's Analysis Solutions Business Area. Our talented team is at the forefront in Security Engineering, Computer Network Operations (CNO), Mission Software, Analytical Methods and Modeling, Signals Intelligence (SIGINT), and Cryptographic Key Management. At Leidos, we offer competitive benefits, including Paid Time Off, 11 paid Holidays, 401K with a 6% company match and immediate vesting, Flexible Schedules, Discounted Stock Purchase Plans, Technical Upskilling, Education and Training Support, Parental Paid Leave, and much more. Join us and make a difference in National Security! Job Summary We are seeking an experienced Data Engineer to execute the design, development and administration of an enterprise-scale Next Generation Correlation/Entity Resolution platform. This position supports a mission-critical system that serves as a foundational data exploitation capability servicing multiple applications/use cases. The ideal candidate will possess deep expertise in master data management, probabilistic matching algorithms and entity resolution, with the technical architecture skills required to optimize match performance at scale. This role supports technical planning, design, development, integration, and verification and validation. This role refines customer roadmaps, enterprise epics, and strategic requir [... source excerpt omitted ...] ents into detailed requirements and actionable user stories. This role coordinates with the team leadership to prioritize user stories that realize customer requirements. Primary Responsibilities: Platform Development & Administration: Design, develop, and maintain probabilistic matching configurations, algorithms, and scoring models to ensure accurate entity resolution across multi-domain data sources. Entity Relationship Management: Analyze and connect records to determine relationships across datasets, creating accurate master data views that improve data quality and compliance readiness. Full Lifecycle Management: Oversee data model design, implementation, testing, deployment, [... source excerpt omitted ...] dexing, partitioning, and query tuning; monitor systems; and conduct capacity planning and performance testing. Collaboration & Leadership: Partner with stakeholders to translate requirements into solutions, document architecture and procedures, and participate in incident response and root cause analysis. Basic Qualifications: Hands-on experience with probabilistic matching and entity resolution solutions, including translating business requirements into technical configurations Strong knowledge of entity resolution concepts, data linkage theory, and matching algorithms (Fellegi-Sunter, distance metrics, phonetic approaches) Expertise in data quality dimensions, tokenization, s