Principal Enterprise Data Architect

How will you contribute?

• Define, maintain and evolve the Enterprise Data Model and entity-relationship architecture across all business systems: CRM/ERP (Salesforce), ERP (NetSuite), Atlassian tools (Jira/Confluence), proprietary product telemetry/usage data, as well as other internal systems.
• Own master data governance: establish policies, standards, ownership/responsibility, definitions, data quality metrics, and lifecycle management for master entities (e.g., Customer, Account, Product, Usage, Finance, Vendor, Employee) and establishing “golden data”.
• Lead and manage the data lake / data warehouse architecture, with primary platform Snowflake and supporting data-ingestion / ETL/ELT pipelines, streaming usage data, telemetry, business system feeds, and operational/financial data.
• Stay on the cutting-edge of AI, SQL, analytics: evaluate and adopt AI-SQL tools (e.g., Cortex or similar), support augmented analytics, facilitate self-service data/analytics for business users, and embed AI/workbench capabilities into the data platform.
• Own and lead a team responsible for enterprise operational and financial reporting & analytics: define KPIs, build dashboards, develop visualization strategy (e.g., Power BI, Tableau, Looker), ensure data accuracy, timeliness and scalability.
• Partner cross-functionally with business systems owners (Salesforce, NetSuite, product telemetry, Atlassian), IT, data engineering, finance, sales, operations and product leadership to ensure alignment of data strategy with business strategy.
• Enforce data governance, metadata management, data lineage, usage tracking, data cataloging, and ensure compliance with applicable standards/regulations (e.g., GDPR, CCPA, SOX where applicable).
• Define and monitor data quality, data security, access controls, and ensure platform scalability, performance and reliability.
• Provide thought leadership on data architecture best practices, mentor senior data & analytics engineers, promote a data-driven culture across the company.
• Develop roadmaps for data architecture, analytics platform evolution, cost control and performance optimization.

What will you bring?

• 10-15+ years’ experience in data architecture / enterprise data management roles (in mid-to large organizations).
• Proven experience working in a SaaS software company (ideally ~$200M-$1B revenue) or similar high-growth technology company.
• Deep experience architecting enterprise data models and entity-relationship designs across multiple systems and domains (customer, product, usage/telemetry, finance, operations).
• Hands-on and strategic experience with data lake / data warehouse platforms—experience with Snowflake is strongly required.
• Experience ingesting and integrating data from CRM systems (Salesforce), ERP systems (NetSuite), Atlassian tools (Jira/Confluence), and product telemetry / usage data systems.
• Strong experience in master data management (MDM) and governance, metadata management, data quality frameworks, data cataloging and data lineage.
• Expertise in analytics and visualization leadership: delivering enterprise reporting, dashboards, KPI frameworks, business partner engagement.
• Experience evaluating and deploying AI/SQL tools, augmented analytics and working with data science/AI teams to operationalize insights (experience with Cortex or comparable tools is a plus).
• Excellent leadership, communication and stakeholder management skills: able to translate business needs into data architecture and analytics solutions and lead a team.
• A Bachelor’s Degree in Computer Science, Information Systems, Data Science, or related field (Master’s preferred) and relevant certifications (e.g., CDMP, TOGAF, or Snowflake certifications) are helpful.
• Strong understanding of security, compliance and data governance in enterprise contexts.