CNA Financial interview preparation.

Strong knowledge of data architecture, relational and NoSQL database concepts, ETL/ELT patterns, dimensional modeling, metadata, and data quality frameworks for enterprise-scale data solutions.

Strong experience designing and building scalable data integration and pipeline solutions with a focus on accuracy, observability, resiliency, performance optimization, and ease of consumption.

Proficiency in Java / Java Spring Boot / Java Spring Batch, advanced SQL for large-scale, complex datasets, with hands-on experience using AI-assisted development tools to accelerate coding, testing, troubleshooting, and engineering productivity.

Proven experience designing and implementing vector databases (e.g., Vertex AI Vector Search, Pinecone, pgvector), embedding pipelines, and knowledge graph structures that underpin RAG and semantic search applications

Expertise in building ML platforms and data pipelines at scale; familiarity with major ML algorithms, deep learning, NLP, information retrieval, and data mining techniques

Experience with GCP services (Vertex AI, Dataflow, BigQuery, Cloud Run, Pub/Sub); comfort with distributed computing frameworks (Apache Spark, Dataproc) for large-scale data processing.

Bachelor’s degree in security management, criminal justice, risk management, business, safety, emergency management, or a related discipline; advanced degree preferred

A demonstrated commitment to continued professional education and development, staying current with the evolving security, technology, and regulatory landscape relevant to the organization’s industry and global footprint.

Ten or more years of progressively responsible corporate security, safety, law-enforcement, public-sector security, risk-management, or related experience, including significant leadership responsibility.