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.