Principal Data Architect

Responsibilities

• Design and evolve enterprise data architecture across lakehouse, data warehouse, pipeline, and semantic layers
• Translate high-level architectural strategy into actionable technical plans, including epics, features, and sprint-ready stories
• Lead technical design discussions and identify dependencies, risks, and tradeoffs to drive predictable delivery
• Establish and enforce best practices for data modeling, pipeline design, data quality, and taxonomy
• Mentor engineers by providing architectural guidance and elevating system-level thinking
• Design and build scalable data pipelines and semantic models using Microsoft Fabric and Azure
• Support modernization efforts, including migrations from on-prem SQL Server to cloud-based platforms
• Partner with Data Scientists to productionize and operationalize machine learning models

Requirements

• Deep expertise in modern data architectures, including lakehouse and data warehousing
• Strong experience with Microsoft Fabric and Azure data services (Synapse, Data Factory, Azure SQL, OneLake)
• Advanced proficiency in Python, SQL, and Spark
• Demonstrated ability to define architecture standards and design patterns
• Experience working within Agile environments and translating architecture into deliverable work
• Strong understanding of data modeling, governance, and data quality frameworks
• Hands-on experience with cloud migration from on-prem environments
• Ability to act as a technical leader and mentor across multiple teams

Benefits

• Opportunity to collaborate with a diverse group of colleagues in a creative environment
• Progressive career journey and opportunities for advancement
• Continuous development through training, mentorship, and certification programs
• Exposure to modern technologies across various industries
• Fully remote work environment

About the Company

Sparq is a modern product engineering partner that blends strategy, craftsmanship, and speed to help organizations modernize confidently in the age of AI. We turn complexity into clarity across data ecosystems, digital products, and AI acceleration.