Manager Data Engineering job opportunity at The Hartford.

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The Hartford Manager Data Engineering
Experience: 4-years
Pattern: full-time
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loacation Hartford, CT, United States Of America
loacation Hartford, CT....United States Of America

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 member of the   ASM   team , you will directly   impact   written   premium   by ensuring the modeling team can find new insights and deliver them to market rapidly. We are a forward-focused organization that fosters collaboration, encourages creative design, and offers abundant opportunities for visibility, allowing candidates to shape innovative solutions and   showcase   their talents to a wide audience.       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. Our team's culture is deeply rooted in embracing   emerging   technologies and empowering you to select the   optimal   tools for each unique project, so curiosity and adaptability are highly valued. Strong candidates will also   demonstrate   a solid foundation in data management, software engineering, and process automation along with an enthusiasm for delivering efficient solutions to partners.       Responsibilities:     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 management skills   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 accesses technical issues and risks that could   impact   speed, functionality, flexibility, or clarity.   Use Enterprise GitHub for version control, documentation, code collaboration, and technical project management    This role will have a Hybrid work schedule, with the expectation of working in an office (Columbus, OH, Chicago, IL, Hartford, CT or Charlotte, NC) 3 days a week (Tuesday through Thursday).     Minimum Qualifications:     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 into business solutions and strategies as well as turn business requirements into a technical solution    Curious and passionate   for   R&D and innovation               Preferred Skills and Experience:     Bachelor’s or Master's   degree in related discipline or 5+ years of equivalent experience in relevant engineering roles   AWS Certification or experience with AWS Services (S3, EMR, etc.) is strongly preferred   Experience with Insurance data, especially with Actuarial data processes, is preferred    Experience with R AND Python is preferred   Exposure to Machine Learning, Statistical Modeling, or   MLOps   in a business context is preferred   Proficiency   in Automation tools (Airflow, Cron, Autosys, etc.) is a plus   Experience with Cloud data warehouses, automation, and data pipelines ( i.e.   Snowflake, Redshift) is a plus   Experience building CICD pipelines or IAC (Infrastructure as Code) desired       Candidate must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position. Compensation The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is: $127,200 - $190,800 Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age About Us  |  Our Culture  |  What It’s Like to Work Here  |  Perks & Benefits

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