Principle Data Architect - Data & Analytics

Allan Myers, Inc•Worcester Township, PA

4d•Onsite

About The Position

The Principal Data Architect – Data & Analytics is the organization’s highest-level technical authority for enterprise data architecture, responsible for defining, governing, and advancing the long-term data, analytics, and AI strategy. This role serves as the senior-most subject matter expert (SME) for Microsoft Fabric, OneLake, advanced analytics, and Copilot-enabled architectures, ensuring the enterprise is positioned to fully leverage data as a strategic asset. The Principal Data Architect operates at both a strategic and deeply technical level—shaping enterprise architecture decisions, setting non-negotiable standards, and solving the most complex data and integration challenges. This role partners closely with Senior leadership, Infrastructure, security, and Business Application teams to drive scalable, secure, and future-ready data and AI capabilities across the organization.

Requirements

8 -15+ years of progressive experience in data architecture, enterprise architecture, advanced analytics, or platform engineering.
Extensive hands-on experience designing and governing enterprise-scale data platforms in cloud environments.
Proven experience leading enterprise data strategy, architecture governance, and large-scale modernization initiatives.
Enterprise Architecture Expertise: Deep mastery of enterprise data architecture patterns, including lakehouse, data mesh, event-driven, and domain-oriented designs.
Microsoft Fabric Mastery: Expert-level knowledge of Microsoft Fabric, OneLake, Power BI, semantic modeling, and advanced analytics workloads.
AI & Copilot Enablement: Proven experience architecting data platforms that support AI, machine learning, and generative AI at scale.
Advanced Data Modeling: Expert-level proficiency in analytical, operational, and domain-driven data modeling.
Integration & Interoperability: Deep experience with large-scale data integration, APIs, streaming platforms, and hybrid architectures.
Security & Governance: Advanced understanding of data security, privacy, lineage, compliance, and risk management.
Strategic Problem Solving: Ability to solve highly complex, ambiguous architectural challenges.
Leadership & Influence: Ability to set direction, mentor senior talent, and shape enterprise-wide outcomes.
Communication Excellence: Ability to articulate complex technical concepts clearly to executive and non-technical audiences.

Nice To Haves

Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or related field; Master’s degree strongly preferred.
Advanced Microsoft certifications such as Fabric Analytics Engineer, Fabric Data Engineer, Azure Solutions Architect Expert, or equivalent strongly preferred.
Demonstrated ability to operate as a senior technical authority across multiple domains.
Exceptional communication and executive-level presentation skills.
Proven ability to influence architectural direction without direct authority.

Responsibilities

Enterprise Data & AI Strategy Leadership: Own and evolve the enterprise-wide data, analytics, and AI architecture strategy, ensuring alignment with business objectives, digital transformation initiatives, and long-term technology roadmaps.
Microsoft Fabric & OneLake Authority: Serve as the definitive technical authority for Microsoft Fabric architecture, including OneLake, lakehouse design, real-time analytics, semantic models, and AI-enabled workloads at enterprise scale.
Copilot & AI Architecture Enablement: Define advanced data architectures, governance models, and data products required to safely and effectively enable Copilot, generative AI, and machine learning use cases.
Architecture Governance & Standards: Establish and enforce enterprise data architecture standards, guardrails, reference architectures, and design patterns across all data platforms and initiatives.
Complex Solution Architecture: Lead the design and review of the organization’s most complex, high-risk, or high-impact data solutions, resolving architectural trade-offs related to scale, performance, security, and cost.
Data Platform Evolution: Drive modernization of legacy data platforms toward cloud-native, lakehouse, and event-driven architectures.
Advanced Data Modeling: Define and govern enterprise conceptual, logical, and physical data models, including domain-driven and analytical modeling strategies.
Data Integration & Interoperability: Architect enterprise-scale data integration strategies, including APIs, streaming/event platforms, and cloud integrations (e.g., Boomi).
Security, Privacy & Compliance Leadership: Partner with security and risk teams to embed data security, privacy-by-design, lineage, and compliance controls into all data architectures.
Performance, Scalability & Cost Optimization: Set architectural direction for performance tuning, workload optimization, capacity planning, and cost management across data platforms.
Technology Evaluation & Innovation: Evaluate emerging data, analytics, and AI technologies; provide strategic recommendations and proofs of concept to guide adoption decisions.
Executive & Cross-Functional Influence: Advise senior leaders on data and AI capabilities, risks, and trade-offs; translate business strategy into actionable architectural direction.
Technical Mentorship & Thought Leadership: Mentor programmers/developers and analysts to raise the overall technical maturity of the organization through guidance, reviews, and knowledge sharing.
Architecture Documentation & Decision Records: Maintain authoritative enterprise architecture documentation, including standards, roadmaps, and architectural decision records (ADRs).