At Liberty Mutual, our purpose is to help people embrace today and confidently pursue tomorrow. Thats why we provide an environment focused on openness, inclusion, trust and respect. Here, youll discover our expansive range of roles, and a workplace where we aim to help turn your passion into a rewarding profession. We value your hard work, integrity and commitment to make things better, and we put people first by offering you benefits that support your life and well-being. To learn more, please visit https://www.libertymutualgroup.com/about-lm/careers/benefits
Liberty Mutual has proudly been recognized as a Great Place to Work by Great Place to Work US for the past several years. We were also selected as one of the 100 Best Places to Work in IT on IDGs Insider Pro and Computerworlds 2020 list.
We have been named by Forbes as one of Americas Best Employers for Women and one of Americas Best Employers for New Graduatesas well as one of Americas Best Employers for Diversity. To learn more about our commitment to diversity and inclusion please visit: https://jobs.libertymutualgroup.com/diversity-inclusion
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We deliver our customers peace of mind every day by helping them protect what they value most. Our passion for placing the customer at the center of everything we do is driving a transformational shift at Liberty Mutual. Operating as a tech startup within a Fortune 100 company, we are leading a digital disruption that will redefine how people experience insurance.
Job Introduction:
This Senior Data Engineer will join an energetic and engaged data engineering team focused on delivering exceptional value to Global Finance Technology data platforms and execution of the GFT Data Strategy. This role will be responsible for developing an innovative reporting strategy for the GRM E/W countries on SAP S/4HANA. This candidate will also be responsible for contributing to the development of the new GFT data hub, Finance Data Resources (FDR), and driving the prioritization of GRM use cases for FDR. This candidate will receive general direction and is competent to work at the highest level of analysis and design of data models. Leads the data deliverable portion of projects, including developing the data backlog, mentoring and leading junior team members, and reporting out on progress and blockers. Works with IT management and staff to establish and maintain consistent data element definitions across environments. Writes and maintains detailed ETL requirements as well as owns responsibility of thorough end-to-end testing.
About the job:
- Participates in the evaluation of complex business and data requirements
- Transforms common system requirements into data models for shared and reusable services according to architecture, technology and standards agreed upon by the team
- Identifies and consults on moderate-high complexity data structure and/or data content issues and develops effective data solutions
- Effectively understands and communicates data objectives, scope and direction across project teams and stakeholder groups
- Actively researches & resolves test issues and data content
- Drives ownership and responsibility of end-to-end solution in alignment with agreed upon architecture
- Investigates and makes final recommendations on new tools, techniques, and software
- Advocates for and leads agile practices for working with the team and our business partners, leveraging Jira as the primary source to track and communicate work efforts
- Demonstrated experience delivering data solutions via agile methodologies
- Requires critical thinking, data analysis, and data modeling experience
- Strong leadership, communication, collaboration skills with a track record of taking solution ownership
- Must be proficient in Python and SQL
- Experienced developing database solutions on AWS: Redshift, Aurora, RDS, etc.
- Experience with ETL as code: Glue, Lambda, etc.
- Demonstrates leadership and active pursuit of optimizing data and reporting processes
- Thorough knowledge in the following areas; commercial P&C insurance, general IT concepts, strategies and methodologies, thorough knowledge of new data architecture principles and concepts, thorough understanding of layered systems architectures, extensive knowledge of business operations, strategies and objectives.
