Data Architect

Orion Innovation•Edison, NJ

About The Position

Orion Innovation is seeking a senior Data Architect to lead the architecture, analytics, and AI-ready data strategy for enterprise platforms. The role combines deep expertise in Azure Databricks, Microsoft Fabric, knowledge graphs, and ontologies with architectural leadership, strategic thinking, and client-facing communication. The architect will define a data and AI vision, turn it into an actionable technology roadmap, and lead teams delivering scalable solutions. The position includes designing and evolving enterprise-scale data and analytics platforms; establishing standards, best practices, and reference architectures; and addressing data scalability, performance, governance, security, and interoperability. It also focuses on organizing and contextualizing enterprise data for AI agents and agentic applications, using structured and unstructured data, semantic models, metadata-driven architectures, RAG, GraphRAG, semantic retrieval, and context engineering. The Data Architect will guide platform strategy and modernization, assess current capabilities and architectural gaps, define target-state architectures, and develop phased roadmaps aligned with business priorities. This is a senior client-facing leadership role involving engagement with client architects, technology leaders, and business stakeholders, as well as mentoring data architects and facilitating design reviews and strategic planning sessions.

Requirements

15+ years of experience in data engineering, data architecture, enterprise analytics, or related technology domains.
Proven experience leading enterprise-scale data architecture and modernization initiatives.
Deep hands-on architectural expertise in Azure Databricks, including Lakehouse architecture, Delta Lake, Spark, and large-scale data processing.
Strong working knowledge of Microsoft Fabric, its architecture and capabilities, and integration with enterprise data ecosystems.
Solid understanding of ontologies, knowledge graphs, semantic technologies, and enterprise data modeling.
Demonstrated understanding of how enterprise data supports generative AI, AI agents, and context-aware intelligent applications.
Experience designing scalable, secure, and governed enterprise data platforms.
Proven ability to define technology strategy, target-state architecture, and phased implementation roadmaps.
Experience leading teams of data architects and technical specialists.
Excellent client-facing communication, presentation, stakeholder management, and technical storytelling skills.
Ability to work independently, challenge existing approaches, and recommend innovative yet practical solutions.

Nice To Haves

Experience with Microsoft Azure data and AI services, including Azure AI Search, Microsoft Foundry, and related services.
Knowledge of Microsoft Fabric IQ, semantic layers, and emerging enterprise context platforms.
Experience implementing knowledge graphs or ontology-driven enterprise data solutions.
Familiarity with agentic AI frameworks, MCP, and enterprise AI integration patterns.
Experience with complex, globally distributed enterprise environments, particularly regulated industries.
Experience developing enterprise data strategies and presenting them to senior technology executives.

Responsibilities

Lead the architecture and evolution of enterprise-scale data and analytics platforms.
Design scalable data processing, integration, transformation, and analytics solutions using Azure Databricks and Microsoft Fabric.
Establish architectural standards, best practices, and reference architectures for data platforms.
Guide data architects and engineering teams in designing reliable, secure, and high-performance solutions.
Address architectural challenges involving scalability, performance, governance, and interoperability.
Define approaches for organizing, contextualizing, and exposing enterprise data to AI agents and agentic applications.
Design solutions combining structured and unstructured enterprise data to provide business context to AI agents.
Apply RAG, GraphRAG, semantic retrieval, and context engineering concepts.
Establish reusable patterns for exposing trusted enterprise data to AI agents through APIs, tools, and other integration mechanisms.
Architect large-scale Databricks analytics solutions, including distributed processing, Delta Lake, and Lakehouse architectures.
Drive performance optimization, scalability, reliability, and cost efficiency across data platforms.
Evaluate emerging data technologies and recommend adoption based on business value and architectural fit.
Own and communicate the long-term data platform and AI-enablement vision.
Assess existing capabilities, identify architectural gaps, and define future-state architectures and phased technology roadmaps.
Lead client engagements and communicate architectural concepts, recommendations, and trade-offs to technical and non-technical audiences.
Lead and mentor data architects, provide technical direction and architectural governance, and facilitate architecture discussions, design reviews, and strategic planning sessions.
Influence architectural decisions and build stakeholder confidence through technical credibility and a clear vision.