Manager Data Engineering

Manager, Data Engineering (GE07AE
)

We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future.

The Hartford is seeking a Data Engineering Manager to lead a team of Data Engineers to design, develop, and implement modern and sustainable data assets to fuel machine learning and statistical modeling solutions across a wide range of strategic initiatives. The Actuarial Strategic Modeling team is a dynamic mix of Actuarial and Data Science professionals utilizing statistical modeling, machine learning, and advanced data engineering techniques to enhance core Actuarial processes.

As a Data Engineering Manager, you will lead and mentor a small team through the software development lifecycle process, supporting strong programming foundations and cloud operations, and fostering a robust understanding of the analytics behind our work. Collaborating closely with a broader team of talented engineers and data scientists, you will oversee engineering and model support projects across several lines of business, serving as the primary contact for engineering and data solutions.

• Lead and mentor Data Engineers to deliver and maintain reusable and sustainable analytical processes that assist Actuarial Modelers in meeting their strategic objectives
• Learn and coach Machine Learning and MLOps, Engineering, and Insurance Business concepts & terminology, applying that knowledge for the best fit‑to‑purpose solution
• Anticipate team and individual growth needs, identify relevant opportunities and coach direct reports and peers accordingly
• Regularly engage in continuing education, including the development of project and people managementli>
• Consult with cross‑functional stakeholders in the analysis of short and long‑range business requirements and recommend modernization that anticipates future business needs
• Own and lead engineering projects, leveraging agile software development practices to manage work and communicate status
• Assess business needs and lead the development of reliable and effective solutions that are catered to specific business needs and easily maintainable
• Create data assets and build data pipelines that align to modern software development principles for further analytical consumption
• Perform data analysis to ensure quality of data assets
• Design and develop high quality, scalable software modules for next generation analytics solution suite that serves advanced statistical models and tracks key metrics
• Enhance and maintain model and data monitoring solutions that deliver automated insights to technical and non‑technical audiences
• Identify and validate internal and external data sources for availability and quality. Work with SMEs to describe and understand data lineage and suitability for a use case
• Proactively access technical issues and risks that could impact speed, functionality, flexibility, or clarity
• Use Enterprise Git Hub for version control, documentation, code collaboration, and technical project management

• 4+ years of programming experience in a business setting
• Experience in managing Data Engineers or leading Engineering project teams within an Analytics context and in an agile environment
• Interest in deeply learning & understanding the Insurance Business and Actuarial role
• Proficiency in SQL and at least one additional functional or object‑oriented programming language such as R or Python
• Experience with data or process management solutions in the cloud, including data pipelines, automation, and containerized compute
• Proficiency in ingesting data from a variety of structures including relational databases, Hadoop/Spark, cloud data sources, XML, JSON
• Proficiency in ETL concerning metadata management and data validation
• Proficiency with Git in a collaborative business setting
• Proficiency in Linux‑based file management
• Ability to communicate effectively with both technical and non‑technical teams
• Demonstrated ability to translate complex technical topics…