Data Platform Architect

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Job Summary

The Data Platform Architect is responsible for designing and guiding the architecture of Sun’s enterprise data platform, including the data lake, enterprise data warehouse, and surrounding data ecosystem. This role ensures that data is ingested, modeled, stored and delivered in ways that are scalable, secure, reliable, artificial intelligence (AI) ready and aligned with organizational needs. Partnering closely with data engineering, analytics, governance, and application teams, the Data Platform Architect establishes platform patterns, designs canonical and analytical models, and ensures the data platform provides a strong foundation for analytics, business intelligence, data products, and emerging AI workloads. This role influences platform direction, reduces technical debt, prevents fragmentation, and supports consistent, high‑quality data across the enterprise. This position is architecture‑focused rather than hands‑on engineering, with an emphasis on platform design, patterns, alignment, and stewardship.

Job Duties

• Define and maintain the architecture of Sun’s enterprise data platform, including the data lake, enterprise data warehouse, lakehouse components, and downstream analytical use cases. (Essential)
• Establish and promote scalable data platform patterns, such as ingestion architecture (batch, streaming), processing frameworks, and domain‑oriented design. (Essential)
• Design canonical and analytical data models that support enterprise reporting, analytics, and AI workloads. (Essential)
• Review and guide platform data models (conceptual, logical, physical) to ensure alignment, reusability, and consistency across domains. (Essential)
• Set and enforce platform architecture standards and guardrails, balancing innovation with security, quality, and long-term maintainability. (Essential)
• Partner with data engineering, analytics, and product teams to design data structures optimized for business intelligence, analytics, machine learning, and data-driven features.
• Work closely with governance, security, legal, and compliance teams to ensure architecture incorporates data quality, metadata, access controls, and responsible AI principles.
• Evaluate and recommend data platform technologies, providing guidance on performance, scalability, cost, and alignment with long‑term architecture.
• Monitor emerging trends in cloud data architectures, lakehouse technologies, semantic modeling, and AI platform services to inform long‑term roadmap direction.
• Other job duties and special projects as assigned.

Requirements

• High School Diploma or GED (Required)
• Bachelor's Degree in Computer Science, Information Systems, Data Engineering, or related field (Required)
• 8 years in proven experience in data engineering, data architecture, or analytics engineering (Required)
• 5 years in hands‑on exposure to modern cloud data platforms (Required)
• Must have a valid driver's license
• Strong expertise in data modeling (conceptual, logical, physical) and understanding of how models support analytics and AI workloads (Required)
• Demonstrated proficiency with modern cloud data environments such as Databricks, Snowflake, Azure Synapse/Fabric, BigQuery, Redshift (Required)
• Experience defining architecture standards, reusable patterns, and enterprise data platform guardrails (Required)
• Deep understanding of integration patterns (batch, streaming, change data capture) and metadata‑driven design (Required)
• Experience supporting or enabling machine learning or AI platforms
• Ability to influence cross‑functional stakeholders without direct authority
• Strong communication skills and the ability to convey complex architectural concepts to both technical and non‑technical audiences
• Experience working within a federated or domain‑oriented data architecture model (e.g., data mesh principles)