Principle Data Architect

Allan Myers•Worcester, PA

17h•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. This position is not remote. Candidates must live with one hour of our Worcester, PA office and will be required to work in the Worcester, PA office.

Requirements

Education: Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or related field; Master’s degree strongly preferred.
Certifications: 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.
Experience: 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.

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).