• Serves as a key team member who delivers results and creates value for the CNA brand, customers, and internal stakeholders, while collaborating effectively with external and offshore resources as needed.

• Demonstrate hands-on experience using AI-assisted development tools to accelerate engineering tasks such as pipeline creation, code generation, testing, and troubleshooting

• Apply strong engineering judgment when working with AI-generated outputs, ensuring alignment with enterprise standards for quality, security, and data handling

• Design and build data pipelines that support multi-modal data, including structured, semi-structured, and unstructured sources (e.g., transactional data, documents, and external data feeds)

• Build and modernize data pipelines across hybrid environments (on-premiseand cloud), incorporating automation, observability, and resiliency by design

• Designs, builds, and enhances large-scale data processing systems and data lakes on Google Cloud Platform,optimizing forcomputational and storage efficiency while applying strongexpertisein data modeling and engineering best practices.

• Operate effectively in complex, multi-entity and multi-national system landscapes, integrating internal platforms and external data providers

• Bring familiarity with both legacy enterprise data tools (e.g., ETL/ELT platforms, relational databases) and modern cloud-native data and integration services

• This role is not focused on experimentation alone 97 it is focused on applying AI in a disciplined, production-grade engineering environment to drive measurable improvements in delivery speed, quality, and operational reliability

• May lead or sub-lead the design of complex physical data models, projects and cloud-based data lake constructs including SQL/NoSQL database systems.

• May lead or sub-lead the creation of integrated data views based on business or analytics requirements.

• May lead or sub-lead robust unit testing to ensure deliverables match the design and provideexpertiseto supportsubsequentrelease testing.

• Actively adheres toestablishedquality and reliability standards, and ensures team adheres to the same quality and standards working in an Agile development environment.

• Research,identifiesandimplementsprocess improvements that address complex technology gaps. Builds strong knowledge of technology enablers.

• May lead or sub-lead the design and building of data solutions and applications that enable reporting, analytics, data science, and data management.

• Maintains professional and technical knowledge by attending educational workshops; reviewing professional publications;establishingpersonal networks;participatingin professional societies. Drives the evolution of CNA application development processes and standards.

• 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.

• Proficiencyin Python and advanced SQL for large-scale, complex datasets, with hands-on experience using AI-assisted development tools to accelerate coding, testing, troubleshooting, and engineering productivity.

• Strong communication, collaboration, and stakeholder engagement skills, with the ability to apply sound engineering judgment and work effectively across highly matrixed, cross-functional, and global teams.

• Preferred experience building data and analytics solutions on Google Cloud Platform, including services such asBigQuery, Cloud Storage, Dataflow,Dataproc, Pub/Sub, and Cloud Composer, or equivalent cloud-native data technologies.

• Preferred experience in insurance and financial services, including familiarity with regulatory, risk, underwriting, claims, customer, and operational data domains.

• Experience with big data and distributed processing technologies, hybrid cloud andon-premiseenvironments, and modern engineering practices including automation, testing, CI/CD, and secure data handling.

• Working knowledge of business intelligence, reporting, and analytics enablement tools, with an understanding of data governance, lineage, monitoring, and controls needed to support trusted, production-grade data products.

Education & Experience

• Bachelors degree withMasterspreferred in Computer Science, Information Technology, relateddisciplineor equivalent work experience.

• Typically5+ years of experience in data,analyticsor application development.

• 2+ years of codingproficiencyin at least one programming language (Python, Java, SQL).

• Experience using Agile methods preferred.

• Applicable certifications preferred (GCP, Data Engineering).

#LI-KJ1 #LI-HYBRID