Define and maintain the overall technical architecture for the KM data platform spanning ingestion storage (Databricks/Unity Catalog) transformation security and consumption layers.
Translate multi-year program roadmaps into phased architectural plans balancing near-term pilot needs against long-term scalability.
Set architectural standards and guardrails for data modeling pipeline design and catalog registration in partnership with the Senior Data Modeler and Data Engineers.
Evaluate and recommend platform components tools and integration patterns (e.g. Unity Catalog vs. alternative catalogs orchestration tools vector search/embedding infrastructure).
Lead technical design reviews and ensure alignment across data engineering security/privacy and downstream product teams (Knowledge Products Research Products).
Own non-functional requirements: scalability performance security cost and reliability of the platform architecture.
Serve as the primary technical point of contact for architecture workshops and planning sessions (e.g. multi-day cross-functional architecture planning events).
Assess technical risk and dependencies across workstreams and flag issues to the Engineering Manager and program leadership.
Stay current on Databricks platform capabilities and enterprise AI/knowledge management architecture trends bringing recommendations back to the team.
Required Qualifications
8 years of experience in data/solution architecture roles with significant hands-on or architectural experience in Databricks/Lakehouse environments.
Deep understanding of Unity Catalog governance data product design and security classification models.
Demonstrated experience architecting platforms that handle both structured and unstructured content at scale.
Experience architecting for AI/LLM-driven consumption patterns (retrieval-augmented generation vector search agent-based data access) is highly valued.
Strong track record of translating business/program roadmaps into technical architecture and staged delivery plans.
Excellent stakeholder management skills able to work across engineering product legal/privacy and executive audiences.
Experience leading architecture reviews and setting technical standards for a growing engineering team.
Preferred Qualifications
Experience in professional services consulting or other knowledge-intensive industries.
Familiarity with enterprise search/knowledge platforms (Glean SharePoint ServiceNow) and their integration patterns.
Experience navigating legal/risk/privacy review processes for data platforms.
Prior experience standing up a data platform team from a nascent or pilot stage to a scaled production capability. Success Metrics (First 612 Months)
Documented target-state architecture for the KM data platform validated with key stakeholders (Engineering Manager Data Modeler Product Owners).
Architectural standards adopted across data modeling and engineering workstreams.
Clear staged technical roadmap aligned to the broader program timeline (e.g. through 2027).
Qualifications :
Must have skills: Azure Data Factory Data Modeling (Strong) Databricks
Remote Work :
No
Employment Type :
Full-time
Department / Functional Area: Engineering Experience: years Vacancy: 1