Data Architect

Anika Systems is seeking a highly skilled Data Architect to lead the design and implementation of enterprise data architectures supporting federal clients. This role will be instrumental in shaping data strategy, enabling data-driven decision-making, and supporting the establishment and maturation of Office of the Chief Data Officer (OCDO) organizations.

The ideal candidate brings deep expertise in enterprise data modeling, cloud-based data platforms, metadata management, and data governance, along with hands‑on experience applying AI/ML, Knowledge Graphs, and semantic technologies to modern data ecosystems. This role requires a forward-thinking architect who embraces AI-driven development workflows and can integrate emerging techniques such as GraphRAG into enterprise data platforms.

This opportunity is 100% remote.

• 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, Service Now, 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 on data strategy progress, maturity improvements, and program outcomes.
• Continuously refine data architecture based on stakeholder feedback, emerging AI capabilities, and evolving organizational needs.

• Bachelor’s degree in Computer Science, Information Systems, Data Science, or related field…