15+ years of experience in data engineering or architecture
Proven leadership in enterprise-scale data architecture initiatives
Deep expertise in Azure Databricks and Lakehouse architecture
Strong knowledge of Microsoft Fabric and its integration capabilities
Solid understanding of ontologies, knowledge graphs, and semantic technologies
Experience designing scalable and governed enterprise data platforms
Excellent client-facing communication and stakeholder management skills
Responsibilities
Lead the architecture of enterprise-scale data and analytics platforms
Design scalable data processing and analytical solutions using Azure Databricks
Establish architectural standards and best practices for data platforms
Define how enterprise data can be organized for AI accessibility
Architect large-scale data analytics solutions with performance optimization
Own and articulate the long-term data platform and AI-enablement vision
Act as a senior client-facing technology leader, engaging with stakeholders
Benefits
Opportunity to drive innovative data and AI strategies
Work with cutting-edge technologies like Azure Databricks and Microsoft Fabric
Lead and mentor a team of skilled data architects
Engage directly with clients and influence architectural decisions
Develop a clear roadmap for evolving data capabilities
Full Job Description
Experience: 15+ Years
Role: Data Architect - Data & AI Platforms Role Overview
We are seeking an experienced Data Architect to drive the architecture, analytics, and AI-ready data strategy for enterprise platforms.
The ideal candidate will combine deep technical expertise in Databricks, Microsoft Fabric, knowledge graphs, and ontologies with strong architectural leadership, strategic thinking, and client-facing communication skills.
This role requires someone who can define a compelling data and AI vision, translate it into an actionable technology roadmap, and lead architecture teams to deliver scalable solutions. Key Responsibilities
1. Data Architecture & Technical Leadership
Lead the architecture and evolution of enterprise-scale data and analytics platforms.
Design scalable data processing, integration, transformation, and analytical 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, high-performance solutions.
Address architectural challenges involving data scalability, performance, governance, and interoperability.
2. AI-Ready Data & Context Engineering
Define how enterprise data can be organized, contextualized, and made accessible to AI agents and agentic applications.
Demonstrate strong understanding of ontologies, knowledge graphs, semantic models, and metadata-driven architectures.
Design approaches that combine structured and unstructured enterprise data to provide meaningful business context to AI agents.
Understand and apply concepts such as RAG, GraphRAG, semantic retrieval, and context engineering.
Establish reusable patterns for exposing trusted enterprise data to AI agents through APIs, tools, and other integration mechanisms.
3. Data Analytics & Platform Scalability
Architect large-scale data analytics solutions using Databricks, including distributed processing, Delta Lake, and Lakehouse architectures.
Understand Microsoft Fabric capabilities, including OneLake, Lakehouse, Data Warehouse, and semantic models.
Drive performance optimization, scalability, reliability, and cost efficiency across data platforms.
Evaluate emerging data technologies and recommend their adoption based on business value and architectural fit.
4. Strategy, Vision & Roadmap
Own and articulate the long-term data platform and AI-enablement vision.
Assess existing capabilities, identify architectural gaps, and define future-state architectures.
Develop practical, phased technology roadmaps aligned with business priorities.
Identify opportunities to evolve traditional analytics platforms into intelligent, AI-enabled enterprise data ecosystems.
Balance strategic architectural direction with pragmatic delivery considerations.
5. Client Engagement & Team Leadership
Act as a senior client-facing technology leader, engaging with client architects, technology leadership, and business stakeholders.
Clearly communicate complex architectural concepts, technology recommendations, and trade-offs to technical and non-technical audiences.
Lead and mentor a team of data architects, providing technical direction and architectural governance.
Facilitate architecture discussions, design reviews, and strategic planning sessions.
Influence architectural decisions and build stakeholder confidence through strong technical credibility and a clear vision.
Required Qualifications & Experience
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, 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.
Preferred Qualifications
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.
What Success Looks Like
A clear, compelling Data & AI Architecture Vision aligned with business objectives.
A practical roadmap for evolving existing Databricks and Microsoft Fabric capabilities.
A scalable architectural approach for making trusted enterprise data available to AI agents.
Strong architectural leadership and consistent technical direction across data engineering teams.
Recognition as a trusted architectural advisor to client technology leadership.
About Orion Innovation
Orion Innovation is a global technology services firm that provides IT solutions and services to businesses across various industries. The company offers digital transformation, product engineering, data analytics, cloud computing, and other IT services to help businesses improve their operations and achieve their goals. Orion Innovation has offices in the United States, Europe, and Asia, and serves clients in industries such as financial services, healthcare, retail, and more.
