Data Architect, Advisor

Responsibilities

• Define the enterprise data architecture supporting operational systems, analytical platforms, and AI initiatives.
• Establish the event-driven integration patterns, governance and metadata standards, and reusable data products.
• Assess legacy systems to understand data structures, data quality, storage mechanisms, and transformation logic.
• Work closely with the Systems Architect on enterprise direction, with Solutions Architects on product-level data needs, and with Data Engineers.
• Define the target-state data architecture spanning operational stores and the analytical data lake.
• Develop conceptual, logical, and physical data models that support both transactional systems and analytics.
• Design event-driven integration patterns that feed the EDL, using messaging and an enterprise service bus.
• Define reusable data products with clear ownership, documented schemas, lineage, quality expectations, and access policies.
• Define data governance, metadata, and cataloging standards.
• Ensure the data architecture supports analytics, machine learning, and Generative AI use cases.

• Minimum of 8 years with BS/BA
• Minimum of 6 years with MS/MA
• Minimum of 3 years with PhD
• Demonstrated experience in enterprise data architecture across operational and analytical systems.
• Hands‑on experience with at least one modern data engineering stack.
• Strong knowledge of relational and non‑relational databases (e.g., SQL, No
  
  SQL, Hadoop, Spark, Kafka, Kinesis) and data modeling.
• Experience designing event‑driven and streaming data integration.
• Experience with programming languages (e.g., Java, SQL, Scala, Python).
• Experience with schema definition, data governance, metadata management, and data quality practices and software engineering best practices including secure, testable, and maintainable code.
• Experience with cloud data platforms, preferably AWS.
• Active Secret Clearance.
• Local to the Washington, D.C. Metro area.