Senior Data AI Engineer

CNA InsuranceChicago, IL
$72,000 - $141,000Hybrid

About The Position

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.

Requirements

  • 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.
  • 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).

Nice To Haves

  • 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.

Responsibilities

  • 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.

Benefits

  • 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.
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