Data Architect

🕒 Abril 25

🇺🇸 Estados Unidos – Remoto (EUA)

⏰ Tempo Integral

🟠 Sênior

🔴 Especialista

🚰 Engenheiro de Dados

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Anika Systems

SiteLinkedInTodas as Vagas

51 - 200 funcionários

🤝 B2B

🏛️ Governo

🤖 Inteligência Artificial

B2B • Government • Artificial Intelligence

A Anika Systems é um fornecedor de soluções de tecnologia orientado por resultados, especializado em ajudar agências federais a atingir seus objetivos e se preparar para o futuro. A empresa oferece uma gama de serviços, incluindo Dados e Analytics, Automação Inteligente, Desenvolvimento de Aplicativos, Modernização de TI e Engenharia de Nuvem. A Anika Systems colabora com agências federais para criar soluções inovadoras, de longo prazo e capacitadoras, com foco em entregar objetivos com sucesso, dentro do prazo e do orçamento. Suas capacidades incluem estratégia de dados, aprendizado de máquina, transformação em nuvem e muito mais, aproveitando parcerias com plataformas como Microsoft Azure e Red Hat para aprimorar suas ofertas.

Descrição

• 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.

🎯 Requisitos

• 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.

🏖️ Benefícios

• Flexible work arrangements • Professional development opportunities