Data Architect
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Job Description
Data Architect leading enterprise data architecture design and implementation for federal clients. Shaping data strategy and supporting data-driven decision-making with AI-driven workflows.
Responsibilities:
- Design and implement scalable enterprise data architectures leveraging AWS and Apache ecosystem technologies (e.g., Spark, Iceberg).
- Architect modern AI-enabled data platforms, including support for machine learning, LLM integration, and retrieval-augmented generation (RAG) patterns.
- Develop and maintain conceptual, logical, and physical data models, including Entity Relationship Diagrams (ERDs).
- Architect modern data lakehouse and data warehouse solutions using Apache Iceberg and cloud-native services.
- Define and enforce standards for data integration, data quality, and data lifecycle management.
- Design and implement Knowledge Graph architectures, integrating structured and unstructured data sources.
- Design and implement Knowledge Graphs and semantic data layers using ontologies, taxonomies, and linked data principles.
- Apply GraphRAG architectures to enhance LLM-based applications with context-aware, explainable data retrieval.
- Develop and manage ontologies and semantic models to enable interoperability, data discovery, and advanced analytics.
- Integrate AI/ML and generative AI capabilities into enterprise data ecosystems, including vector databases and embedding pipelines.
- Ensure alignment between data architecture and AI governance, including model transparency, traceability, and responsible AI practices.
- Establish and manage enterprise metadata frameworks, including data dictionaries, business glossaries, and technical metadata repositories.
- Lead or support stakeholder listening campaigns to gather input from executives, data leaders, and practitioners across the enterprise.
- Collaborate with stakeholders to identify data challenges, AI use cases, and opportunities for advanced analytics and automation.
- Support analysis of alternatives (AoA) for data and AI tools/platforms, providing recommendations based on cost, capability, and mission fit.
- Track and report on data strategy progress, maturity improvements, and program outcomes.
Requirements:
- Bachelor’s degree in Computer Science, Information Systems, Data Science, or related field or comparable experience.
- 8+ years of experience in data architecture, data engineering, or enterprise data management.
- Demonstrated experience integrating AI/ML or generative AI capabilities into data platforms.
- Hands-on experience with: AWS data services (e.g., S3, Glue, Redshift, Lake Formation) Apache technologies (e.g., Spark, Iceberg, Hive) Relational databases.
- Strong expertise in data modeling and ERD development.
- Experience designing or implementing Knowledge Graphs, ontologies, or semantic data models.
- Familiarity with Graph-based retrieval approaches (e.g., GraphRAG or similar patterns).
- Experience implementing metadata management, data cataloging, and data governance solutions.
- Demonstrated experience supporting federal data strategy initiatives or OCDO organizations.
- Strong understanding of data quality, lineage, observability, and AI data readiness frameworks.
- Proficiency with AI-assisted tools and workflows (e.g., LLM copilots, automated code generation, data augmentation tools).
- Ability to communicate complex technical concepts to non-technical stakeholders.
- U.S. Citizenship required; ability to obtain and maintain a federal clearance.
Benefits:
- Flexible work arrangements
- Professional development opportunities
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