Senior Data Architect

Job Summary

The Senior Data Architect is responsible for architecting Northeastern University’s transition from legacy data structures to a modern, scalable, AI‑ready data architecture. This role conducts deep assessments of existing systems—including Banner, Workday, Salesforce, ServiceNow, Snowflake, and Azure—and designs future-state structures that support data products, analytics, automation, and AI/ML enablement. Establishes enterprise data standards, models, governance structures, and integration patterns, ensuring that data is trustworthy, discoverable, interoperable, secure, and prepared for advanced use cases such as RAG, vector search, semantic layers, and agentic workflows.

**Applicants must be authorized to work in the United States. The University is unable to work sponsor for this role, now or in the future.*

Minimum Qualifications

Knowledge and skills required for this position are typically acquired through the completion of a Bachelor's degree in Information Systems, Computer Science, Engineering, or a related field and ten or more years of progressive experience in data architecture, enterprise data modeling, or data engineering.

• Proven experience modernizing legacy data environments and designing cloud-native, AI-ready data architectures.
• Experience working with large, complex enterprise systems (e.g., Banner, Workday, Salesforce, ServiceNow, Snowflake, Azure).
• Demonstrated leadership in cross-functional initiatives involving data governance, analytics, and platform modernization.
• Ability to translate complex technical concepts into business-aligned architectural decisions.
• Strong communication and data storytelling skills for senior leadership and non-technical stakeholders.
• Effective collaborator with demonstrated ability to drive alignment across distributed teams. Strong problem-solving, analytical thinking, and architectural documentation skills.
• Ability to set and enforce standards, patterns, reusable components, and governance practices

Technical Competencies:

• Expertise in modern data architecture patterns (data products, lakehouse, domain-driven design, semantic layers).
• Deep knowledge of Snowflake, Azure SQL, Databricks, or similar cloud data platforms.
• Proficiency with DBT, Fivetran, Informatica, or equivalent ELT/ETL tools.
• Experience with event-driven and API-based integrations (Kafka, EventHub, microservices).
• Knowledge of AI/ML foundational components: vector databases, feature stores, RAG pipelines, metadata management.
• Strong understanding of data modeling (conceptual, logical, physical), master data management, and data quality frameworks

Key Responsibil

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1) Modern Data Architecture \& Strategy Development

• Assess existing data structures, integrations, and legacy platforms.
• Define the enterprise’s future-state data architecture aligned with AI, automation, and analytics needs.
• Establish standards, patterns, and reusable frameworks

2) Data Modeling, Products \& Platform Enablement

• Create conceptual, logical, and physical data models across domains.
• Partner with data owners to deliver scalable data products.
• Support Snowflake, Azure, Salesforce, Banner, and ServiceNow data alignment

3) AI/ML Enablement \& Advanced Capabilities

• Design datasets and metadata structures supporting AI, RAG, vector search, and agentic workflows.
• Collaborate with AI Studio and analytics teams to enable model training and inference at scale

4) Data Integration, Quality, and Governance

• Lead ingestion architecture, streaming frameworks, and API integrations.
• Implement data quality, lineage tracking, and governance practices.
• Support FERPA, GDPR, and institutional compliance.

5) Serve as trusted advisor to academic and administrative partners

• Communicate roadmaps and architectural decisions to ITS leadership