Senior Data Architect

What you'll do

• Architect the AI Context Layer to serve as the central source of truth for Agentic AI and GraphRAG systems.
• Design and deploy semantic abstraction layers using platforms like Snowflake, Databricks, or Microsoft Fabric.
• Lead the design of unified Canonical Models for foundational data domains like Studio, Finance, and Content Sales.
• Implement lakehouse patterns including stream processing and event-driven pipelines to feed canonical layers.
• Architect MLOps and LLMOps processes to ensure vector embeddings and feature stores are continuously updated.
• Develop automated frameworks for metadata management, data contracts, and semantic version control.
• Implement data quality and identity resolution frameworks to manage complex object hierarchies across the enterprise.
• Manage cloud compute and storage consumption to optimize platform ROI for complex AI workloads.

What we're looking for

• Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Information Technology, or a similar major.
• 5+ years of experience in data engineering and data architecture in a dedicated Enterprise or Domain Architect capacity.
• Proven track record of designing, scaling, and implementing Canonical Models and Semantic Layers on top of massive Enterprise Data Lakes/Lakehouses.
• 5+ years of experience with modern cloud data platforms, specifically Snowflake, Databricks, or Microsoft Fabric, alongside AWS or Azure.
• Advanced skill in Data Modeling across Relational, Dimensional (Kimball), and Data Vault 2.0 or Graph-native frameworks.
• Demonstrated ability to build, maintain, and version-control an ontology or semantic map.
• Solid understanding of FinOps to manage and optimize cloud compute/storage consumption.
• Proficiency in enterprise modeling tools.