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.
• Design 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.

Expectations:

• Perform responsibilities independently with minimal oversight.
• Demonstrate clients core competencies that define how we work, collaborate, and lead. These competencies guide day to day behaviors and decision making, ensuring we instill trust, communicate effectively, value differences and deliver strong results.
• Consistently takes action in alignment with client values.
• Provides regulatory reporting support, as needed, and partners with other departments to implement effective policies and procedures that support the requirements of applicable statutes and regulation.