Principal Data Architect

Title: Principal Data Architect Location: Washington, DC, USA ASRC Federal is a leading government contractor furthering missions in space, public health and defense. As an Alaska Native owned corporation, our work helps secure an enduring future for our shareholders. Join our team and discover why we are a top veteran employer and Certified Great Place to Work™. ASRC Federal Technology Solutions, a subsidiary of ASRC Federal, is seeking a Data Architect to remotely support our DHS program that we are bidding on. This position is contingent upon award. The Data Architect will serve as the lead authority for designing, implementing, and maintaining enterprise data architecture under the ICE Law Enforcement Systems and Analysis (LESA) Data Quality Improvement Support Services contract, ensuring that data structures, models, and governance frameworks strengthen the accuracy, accessibility, and operational usability of mission‑critical systems such as the Enforcement Integrated Database (EID), the EAGLE application, and the Alien Removal Module (EARM). This role develops and enforces data standards, creates scalable data models, and collaborates closely with law enforcement stakeholders, system owners, and technical teams to align data strategies with operational requirements, compliance mandates, and long‑term modernization goals. The Data Architect ensures that data environments are optimized for integrity, performance, and interoperability, enabling reliable analytics, informed decision‑making, and continuous improvement across ICE data systems. Key Responsibilities Lead the design, development, validation, and documentation of data remediation approaches, analytical methods, to support AI/ML solutions. Ensure all data approaches align with the LESA Data Quality Potential Error Inventory and comply with applicable DHS/ICE policies. Develop AI and machine learning models to detect, remediate, and prevent data quality issues, utilizing cleaned and annotated datasets from ongoing remediation efforts. Oversee the integration of AI-driven models, automation scripts, dashboards, and other data quality tools. Collaborate with stakeholders to identify data quality issues, determine root causes, and recommend or implement corrective actions. Facilitate user training and knowledge transfer on analytics and data quality processes. Qualifications Minimum bachelor’s degree in data science, statistics, computer science, engineering, mathematics, or a closely related discipline; an advanced degree (master’s or doctorate) is preferred. At least eight (8) years of experience in data science, advanced analytics, or a closely related field, with hands-on experience designing and implementing analytical solutions in operational settings. Demonstrated experience in applying advanced statistical techniques, machine learning, and AI to real-world datasets; proficient with modern data analytics toolsets (SQL, Python, R, Databricks, etc.); strong communication skills, with the ability to explain technical concepts clearly.