Data Engineer


Headquartered in the heart of downtown Chicago, CNA is a leading commercial and specialty insurer, offering a diverse range of insurance products including Workers Compensation, Property, General Liability, Professional Liability, Cyber Insurance, Surety, and Warranty. We are one of the world leaders in underwriting non-medical professionals, from lawyers and accountants to architects and management consultants.

What CNA offers:

  • A collaborative and growing analytics team with diverse skills and experiences, combined with deep expertise in insurance applications of data and analytics
  • Modern cloud computing environment that enables you to explore data, build and deploy sophisticated processes that impact key areas such as underwriting, pricing, claims management and risk control
  • Sponsorship of continued professional growth through support for attending technical conferences, meetings and symposia

What we are looking for:

The successful candidate will:

  • Work cross functionally at CNA to build next generation data capabilities to enable superior decision support and insight generation
  • Support data and processes for the pricing, underwriting, claims, operations and marketing for an exciting mix of business insurance products

Essential Duties & Responsibilities:

  • Assemble large and complex data sets from disparate data sources into consumable formats that meet business requirements
  • Create efficient and reproducible ETL Data Pipelines using SQL, Python or big data tools such as Spark
  • Work closely with Data Science, DevOps and data management teams to assist with data-related technical issues and support their data infrastructure needs
  • Build and maintain capabilities for data quality control, identify data quality issues and pipeline failures
  • Build exploratory Dashboards/tools for data scientists and business partners that can be deployed relatively quickly and require low maintenance
  • Create streamlined process for geocoding internal data for matching to external sources
  • Collaborate with application owners to help define data collection requirements
  • Work with Data Scientists to understand requirements and help design systems and processes to deliver business value. Research new uses for existing data
  • Build infrastructure required for flexible and scalable extraction, transformation and loading of data from a wide variety of data sources
  • Design and implement functionality, participate in team code reviews, and provide feedback on performance, logic, standard methodologies and maintenance issues to ensure code-level consistency
  • Create production quality code to support deployment of predictive models
  • Produce coherent documentation, metadata, and reports
  • Own data processing pipelines from conception to production deployment.

Required Skills, Knowledge & Abilities:

  • Advanced SQL knowledge and proven experience working with relational databases.
  • Demonstrated experience in manipulating, merging, cleaning, profiling, and preparing large datasets for analytics, from disparate sources
  • Working knowledge of Python, including pandas
  • Experience working with XML and JSON formats
  • Practical experience with version control, preferably git
  • Experience implementing and maintaining ETL and CI/CD data pipelines
  • Ability to write efficient, well documented data wrangling code
  • Intellectual curiosity to find new and innovative ways to solve data management issues
  • Employ an array of technologies and tools to connect systems together
  • Strong analytical, problem solving and critical thinking skills
  • Attention to detail and accuracy of work, ability to spot and correct issues
  • Strong interpersonal and communication skills
  • Drive to continuously improve and learn new tools and methods
  • Ability to work collaboratively with colleagues with diverse perspectives and backgrounds
  • Strong time management skills
  • Capable of operating with little supervision and thinking independently and innovatively

Preferred Skills, Knowledge & Abilities:

  • Experience with data pipeline and workflow management tools such as Airflow
  • Experience with GCP cloud services such as Big Query, Google Storage, Google Cloud Functions
  • Experience with distributed data processing technologies such as Spark
  • Knowledge of R, including the dplyr and data.table packages
  • Experience working with unstructured data
  • Experience working with insurance data
  • Familiarity with data dash-boarding tools such as Python dash, R Shiny, or Tableau
  • Experience in extracting meaningful information from data using visualization

Reporting Relationship: 

Director or above

Education & Experience:

  • Bachelor’s degree, with two or more years of relevant work experience.


Information Systems

Primary Location

United States-Illinois-Chicago


Technology Executive

Job Posting

Oct 23, 2019

Unposting Date


Read Full Description
Confirmed 19 hours ago. Posted 30+ days ago.

Discover Similar Jobs

Suggested Articles