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Data Engineer, Property Casualty Insurance
2 months ago
You will use your technical aptitude to develop, update, and execute automated data gathering, manipulation, and reporting to ensure we meet all of our data reporting requirements on time, on budget, as well as being responsible for curating data from a variety of diverse modern and legacy systems.
You will utilize modern approaches to understand and update/rebuild older processes (examples of old and new: SAS, Focus, Mainframe, Tableau, Excel, SQL, Business Objects, Python, Essbase, QueryWizard, Cobal, and InSync) while ensuring that data quality, completeness, and timeliness of mandatory reporting is not impacted. This position requires a high degree of competency both in self-motivation and team collaboration, as well as hands on data engineering work. The keywords for success in this role are accuracy, completeness, collaboration, understanding, balancing, and timeliness. Our tasks must be completed on time, be fully accurate, and balance to our other financial systems.
You will work closely with Business Compliance, Corporate Compliance, Actuary, Controllers, Accounting, and other Data areas to ensure the data you report is correct, complete and balanced. You will also be self-directed in writing replacement code and data gathering processes, working to identify, understand and improve/modernize multiple existing data calls and environments (especially mainframe/FOCUS based environments) to use a more modern approach to provide more flexible, easier to navigate, more automatable solutions and as a result to provide more readily accessible data to our business partners and regulatory agencies. A key responsibility is the collection, curation, and balancing of data across all property casualty lines of business (Commercial, Farm, Home, Auto, Umbrella, etc...).
This position offers a hybrid work schedule and is based out of our corporate offices in Bloomington, IL.
How does a Property Casualty Business Intelligence Senior Data Engineer make an impact?
- Develops data pipelines that are scalable, repeatable and secure and can be used for dashboard development, machine learning models and exploratory data analysis.
- Designs and builds data models in Entity Relationships Diagram (ERD).
- Prepares and manipulates data. Manages data migrations/conversions and troubleshoots data processing issues.
- Iteratively delivers functionality using DevOps tools and concepts.
- Collaborates with other areas to develop standards and best practices for research, analysis, data engineering and machine learning.
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