Data Architect

Responsibilities

• Define, maintain, and evolve the core data architecture, including conceptual, logical, and physical data models, data flows, integration patterns, and platform standards.
• Create simple, scalable data flows: Source systems → ingestion → Databricks → consumption.
• Establish foundational data models (bronze / silver / gold or equivalent).
• Define standards for data ingestion, transformation, naming conventions, modeling conventions, access and security, and architectural patterns.
• Translate business and analytics needs into practical data designs and patterns.
• Work closely with technology teams on data solutions, focusing on data modeling, integration, MDM, metadata, data warehousing, data lakes, BI, and related domains.
• Support early analytics, BI, and data science use cases.
• Guide engineers and analysts on best practices in Databricks.
• Maintain data architecture roadmaps and priorities.
• Balance short-term delivery with long-term scalability, articulating tradeoffs, costs, and benefits of different options.
• Identify technical debt early and propose incremental improvements.
• Act as a hands-on advisor to resolve complex data issues, not just a governance role.
• Evaluate emerging technologies and industry trends to guide future investments and modernization efforts.

Requirements

• Experience: Minimum of 8-10 years of experience in data architecture including data modeling, data integration, business intelligence (BI), data marts, data lakes and data warehousing, data architecture and data model design.
• Education: Bachelor’s degree in computer science or related technology degree. Professional certificate or a graduate degree highly regarded.
• Preferred Skills: Experience with Databricks, Azure Data Factory, and Power BI. Strong understanding of modern cloud data architecture, medallion architecture (bronze, silver, gold), and ELT patterns. Must be able to work and travel independently, manage multiple and competing demands.