Data Engineer

Liberty Mutual Insurance•Boston, MA

1d•Hybrid

About The Position

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. Data Solutions is a key team within Global Finance Technology, supporting the flagship LII OneGL program. We are building complex data pipelines to extract data from numerous source systems, transform the data to meet business requirements, and prepare it for loading into the SAP FPSL platform. Collaborating closely with Product Owners and Business users, we iterate quickly to ensure accuracy and reliability as we move towards a Production launch. Looking ahead, Data Solutions will be on the front lines for integrating LII OneGL data into the organization's North Star Architecture, leveraging AWS, Snowflake, PostgreSQL, Power BI, Erwin for data modeling, and IDMC for data governance — all to unlock insights through analytics, generative AI, and more. Data Solutions is looking to add a dynamic Senior Data Engineer to the Data Prep team. This candidate will fill a key hands-on role writing SQL, developing stored procedures, designing transformations, and collaborating across the program. The ideal candidate is well-rounded in Data Engineering concepts, comfortable with cross-team collaboration, and able to translate business requirements into effective data solutions. We are seeking a team member who is self-motivated, willing to learn and upskill as needed, and has a willingness to accept peer review and mentor others. This role involves collaborating with the team, product owners, and business users to maintain and enhance a critical data platform used for both operational and analytical purposes. It also includes designing, building, and supporting data ETL/ELT pipelines, utilizing data modeling and governance, supporting programmatic elements within the system, leveraging data for analytics and reporting, identifying and implementing process improvements, building strong knowledge of technology, mentoring others, following best practices for Production support, making recommendations for data improvement, challenging the status quo, and leveraging generative AI tools for efficiency.

Requirements

Strong SQL expertise
Strong experience with stored procedures
Python
PostgreSQL
Snowflake
Amazon AWS
FCS
Power BI
Bachelor`s degree in technical or business discipline or equivalent experience
Minimum 3+ years of Data Engineering experience
Knowledge of a variety of data platforms/tools such as Snowflake and IDMC
Experience with Python or Java, SQL, and AWS (S3, etc.) and AI technologies
Extensive knowledge of IT concepts, strategies, methodologies
Experience working with agile methodologies and cross-functional teams (Product Owners, Scrum Masters, Developers, Test Engineers)
Must be proactive, demonstrate initiative, and be a logical thinker
Must be team oriented with strong collaboration, communication, prioritization, and adaptability skills required

Nice To Haves

Excited by trying new technology and learning new tools
Understanding of Cloud / Hybrid data architecture concepts
Understanding of insurance industry products
Experience developing back end, database/warehouse technology solutions
Demonstrates leadership and active pursuit of optimizing CI/CD process and tools, testing frameworks and practices

Responsibilities

Writing SQL
Developing stored procedures
Designing transformations
Collaborating across the program
Collaborates with team, product owners, and business users to maintain and enhance a critical data platform used for both operational and analytical purposes
Designs, build, and support data ETL/ELT pipelines using tools such as FCS and IDMC
Utilizes data modeling and governance to conceptualize and implement data transformations and integrations necessary to meet business needs
Supports programmatic elements within system, such as stored procedures and other database logic
Leverages data for analytics and reporting
Identifies and implements process improvements
Builds strong knowledge of technology and mentors others
Follows best practices for Production support
Makes recommendations for how to improve data
Challenges status quo and is focused on continuous improvement
Leverages generative AI tools to work efficiently