Enterprise Data Architect

APN Consulting, Inc. is a progressive IT staffing and services company offering innovative business solutions to improve client business outcomes. We focus on high impact technology solutions in ServiceNow, Fullstack, Cloud & Data, and AI / ML. Due to our globally expanding service offerings we are seeking top-talent to join our teams and grow with us.



Role: Enterprise Data Architect

Location: Remote

Duration: Contract

Role Summary
Lead the definition and governance of enterprise data architecture, ensuring scalable, secure, reusable, and AI-ready data foundations aligned to a code-first, data product-driven model.



Key Responsibilities

• Define enterprise data architecture, canonical data models, and semantic layers
• Design Fabric-based Lakehouse architecture aligned to medallion principles
• Establish architecture guardrails for ingestion, transformation, quality, lineage, and access
• Define data product operating model, including lifecycle, certification, and ownership
• Define code-first engineering standards, including:

o Python-based transformation frameworks
o Notebook vs. pipeline design guidelines

• Establish GitHub repository structure, branching strategy, and environment design
• Define standards for:

o Notebook productionization
o Code modularization and reusable libraries

• rchitect CI/CD patterns and controlled deployment strategies
• Define integration patterns across ERP, MES, OT, historian, and enterprise systems
• Ensure data platforms are AI-ready and agent-consumable
• lign architecture with governance, including change control and approval workflows
• Guide cross-functional alignment across engineering, BI, AI, and business teams

Required Skills

• Deep expertise in Azure, Microsoft Fabric, ADF, Synapse, SQL, and lakehouse architecture
• Strong knowledge of data governance, metadata, lineage, and semantic modeling
• Experience designing enterprise-scale data platforms and reusable data products
• Strong architecture governance and leadership capabilities
• Preferred Background
• Manufacturing domain experience
• Experience with AI-ready data, GenAI, MLOps, or agent-based design
• SAP and enterprise integration exposure

We are committed to fostering a diverse, inclusive, and equitable workplace where individuals from all backgrounds feel valued and empowered to contribute their unique perspectives. We strongly encourage applications from candidates of all genders, races, ethnicities, abilities, and experiences to join our team and help us build a culture of belonging.