vectorized formats · Strong SQL skills for analytical queries, performance tuning, and data modeling (star/snowflake schemas, dimensional modeling, partitioning, clustering). · Unstructured data & AI/RAG: Understanding of vector databases (e.g., Elasticsearch, Milvus, pgvector), embedding models, and RAG architectures. Familiarity with document processing pipelines, chunking strategies, and semantic search … features. · Can structure and run POCs with clear success criteria, timelines, and executive readouts to accelerate technical win. · Competitive positioning · Understands the broader data & AI ecosystem and can articulate differentiation versus other data warehouses, data lake/lakehouse platforms, and analytics tools. 5+ years in a customer-facing technical role ...