
Senior Data AI Engineer
Role summary
CNA is seeking a Senior Data AI Engineer, an individual contributor role focused on designing, building, and modernizing production-grade data pipelines and solutions in hybrid cloud and on-premise environments. This role leverages AI-assisted development tools and modern data engineering practices to integrate diverse data sources across complex enterprise ecosystems. The engineer will optimize large-scale data processing systems on Google Cloud Platform, ensuring scalability, security, and reliability. The position emphasizes applying AI in a disciplined, production-grade engineering setting to enhance delivery speed, quality, and operational reliability, with potential leadership in data modeling and testing.
You have a clear vision of where your career can go. And we have the leadership to help you get there. At CNA, we strive to create a culture in which people know they matter and are part of something important, ensuring the abilities of all employees are used to their fullest potential.
Senior Data/AI Engineer is an individual contributor role responsible for designing, building, and modernizing production-grade data pipelines and data solutions across hybrid cloud and on-premise environments. The role applies expertise in AI-assisted development tools, strong engineering judgment, and modern data engineering practices to integrate structured, semi-structured, and unstructured data across complex enterprise ecosystems, leveraging both legacy platforms and cloud-native technologies to deliver scalable, secure, resilient, and high-quality solutions that improve speed to delivery, operational reliability, and business value.
JOB DESCRIPTION:
Essential Duties & Responsibilities
*Performs a combination of duties in accordance with departmental guidelines:*
- 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-premise and 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 for computational and storage efficiency while applying strong expertise in 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 — 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 provide expertise to support subsequent release testing.
- Actively adheres to established quality and reliability standards, and ensures team adheres to the same quality and standards working in an Agile development environment.
- Research, identifies and implements process 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; establishing personal networks; participating in professional societies. Drives the evolution of CNA application development processes and standards.
*May perform additional duties as assigned.*
Reporting Relationship
Typically Director or above
Skills, Knowledge & Abilities
- 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 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 as BigQuery, 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 and on-premise environments, 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
- Bachelor’s degree with Master’s preferred in Computer Science, Information Technology, related discipline or equivalent work experience.
- Typically 5+ years of experience in data, analytics or application development.
- 2+ years of coding proficiency in at least one programming language (Python, Java, SQL).
- Experience using Agile methods preferred.
- Applicable certifications preferred (GCP, Data Engineering).
#LI-KJ1 #LI-HYBRID
*In certain jurisdictions, CNA is legally required to include a reasonable estimate of the compensation for this role. In District of Columbia, California, Colorado, Connecticut,* *Illinois*, *Maryland,* *Massachusetts*, *New York and Washington,* *the national base pay range for this job level is $72,000 to $141,000 annually. Salary determinations are based on various factors, including but not limited to, relevant work experience, skills, certifications and location. CNA offers a comprehensive and competitive benefits package to help our employees – and their family members – achieve their physical, financial, emotional and social wellbeing goals. For a detailed look at CNA’s benefits, please visit [cnabenefits.com](http://cnabenefits.com).*
CNA utilizes AI-enabled technology during the recruiting process. For more information, please visit our [careers page](https://www.cna.com/careers).
CNA is committed to providing reasonable accommodations to qualified individuals with disabilities in the recruitment process. To request an accommodation, please contact [leaveadministration@cna.com](mailto:leaveadministration@cna.com)
