Description

1. Experience Depth: Has designed and delivered large-scale data platforms, models, and pipelines. Remains hands-on with SQL/Python and can explain production issues they personally resolved.
2. AI/RAG/Agentic Understanding: Can design the data foundations for RAG and agentic workflows: document processing, metadata, chunking, embeddings, and vector indexing. Explains how data quality, freshness, and permissions affect retrieval accuracy.
3. Enterprise Solution Design: Has designed conceptual, logical, and physical data models and integrated enterprise sources using ETL/ELT batch, streaming, or CDC patterns. Can explain choices around semantic models, warehouse/lakehouse design, lineage, quality, and access controls.
4. Customer-Facing Ability: Has led data discovery workshops with business owners, data teams, and engineers. Turns unclear requirements and fragmented source systems into practical data designs, ownership agreements, and measurable quality expectations.
5. Leadership/Mentoring: Mentors engineers on modeling, pipelines, governance, and Al data preparation. Reviews implementations, troubleshoots alongside delivery teams, and creates reusable integration patterns and modeling standards.
6. Communication: Explains complex data flows, models, and quality issues clearly to business and technical audiences. Uses concrete examples to explain tradeoffs and their impact on Al outputs and customer outcomes

Key Skills

Education

Bachelor's degree