Data Engineer Specialist

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.