remote
Data Architect - Anika Systems
Software Engineer
Lead the design and implementation of enterprise data architectures for federal clients, shaping data strategy and enabling data‑driven decisions using cloud platforms, metadata management, governance, and AI/ML‑powered knowledge graphs.
About the role
- 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.
- Leverage AI-assisted development tools (e.g., code generation, data pipeline automation, metadata enrichment) to improve delivery speed and quality.
- 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.
- Support implementation or optimization of Enterprise Data Resource Management Systems (EDRMS) and data catalog tools (e.g., Collibra, ServiceNow, or similar platforms).
- Ensure referential integrity and traceability between data assets, metadata, ontologies, and enterprise data initiatives.
- Design systems that enable data lineage, observability, and quality monitoring, including AI-generated metadata and lineage tracking.
- 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 the development and maintenance of data governance frameworks, policies, and standards, including AI and semantic governance.
- Maintain and prioritize a data initiatives backlog, ensuring alignment with mission needs and stakeholder priorities.
- Work within Agile frameworks to iteratively deliver data architecture and AI-enabled solutions.
- Support analysis of alternatives (AoA) for data and AI tools/platforms, providing recommendations based on cost, capability, and mission fit.
- Track and report