Data Architect - Analytics

The Data Architect – Analytics will serve as the architectural lead responsible for modernizing data processes and enabling standardized workflows across multiple regions.

This role involves partnering with global business and technical teams to define business rules, redesign compensation-related data architectures, and implement scalable, cloud-native solutions in Azure.

T he Data Architect will support multi-year transformation initiatives and ensure the integrity, auditability, and extensibility of analytical and compensation workflows.

• Engage with business users across North America and Europe through workshops and data discovery sessions.
• Drive alignment on business rules, data definitions, and data sources across regions with differing processes.
• Serve as an architectural thought leader, guiding teams from manual processes to standardized, modernized workflows.
• Collaborate closely with business analysts, data analysts, product owners, and engineering teams across geographies.
• Lead the re-architecture of compensation data processing, including internal and external data flows, into a scalable Azure environment.
• Define architectural patterns, frameworks, and integration strategies across Azure services such as Data Factory, Databricks, Data Lake, and SQL.
• Evaluate and improve rules engine usage to externalize business logic formerly embedded in application code.
• Guide decisions to shift logic and data ownership into enterprise-owned systems.
• Analyze current-state processes and identify opportunities for re-engineering, automation, and consolidation.
• Assess and rationalize upstream and downstream file integrations to support modern orchestration and MDM strategies.
• Support a multi-year transformation roadmap with multiple Scrum teams delivering high-accuracy systems.
• Lead design of impact analysis capabilities to help the business understand how organizational or portfolio changes affect compensation outcomes.
• Ensure architectures support extensibility, auditability, and traceability.

• 12+ years of experience with Azure.
• 12+ years of experience with Databricks.
• 12+ years of experience in data modeling.
• Demonstrated experience in team leadership.
• Experience conducting client interviews and stakeholder discussions.