Senior Data Architect

About the role

The Senior Data Architect will design and scale our unified data ecosystem, transitioning from siloed systems to a modern Lakehouse architecture. This role will define the data models and architecture that connect Salesforce (CRM), Sage Intacct (ERP), and product telemetry into a high-performing Databricks environment, ensuring data is a strategic asset across the business.

This role is ideal for a systems thinker and data strategist who can connect complex data ecosystems and enable Everway to unlock the full value of its data.

Main responsibilities

• Design Unified Data Models: Create conceptual, logical, and physical models that connect customer, product, and financial data across systems
• Lead Lakehouse Architecture: Define and scale Databricks architecture (Bronze/Silver/Gold layers) to support analytics and AI/ML use cases
• Drive Data Consistency & Quality: Establish “golden record” standards, data governance, and proactive data quality frameworks
• Enable Lead-to-Cash Visibility: Align CRM and ERP data to support accurate revenue recognition and end-to-end business insights
• Support M&A Integration: Develop scalable data onboarding patterns to integrate acquired company data efficiently
• Power Business Insights: Enable use cases across Sales, Product, Support, and Finance through integrated, high-quality data
• Modernize Data Practices: Implement data-as-code, CI/CD for data pipelines, and real-time/event-driven data architecture

Essential criteria

• 5+ years of experience in a senior data architecture role, with strong expertise in cloud data platforms (e.g., Databricks, lakehouse environments)
• Proven experience designing and implementing enterprise-scale data models across multiple systems
• Deep understanding of Salesforce data architecture and integration patterns
• Experience working with cloud ERP systems (e.g., Sage Intacct, NetSuite, Workday) and financial data models
• Strong proficiency in SQL, data modeling (ERD), and data transformation practices
• Experience with data governance, data quality frameworks, and master data management
• Experience in M&A environments, particularly data integration and migration strategies
• Experience with Databricks Lakehouse architecture, including Unity Catalog and medallion design patterns
• Ability to translate complex data concepts into clear business value for technical and non-technical stakeholders

Desirable criteria

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