Description
If you are passionate about data engineering and want an opportunity to work with the latest technologies, then Modeling Data Solutions has the position for you.
Modeling Data Solutions is seeking experienced data analytics engineers to join its Personal Lines Property and Small Commercial Package teams in our Data Solutions job family. This is an exciting opportunity to join the US Data Science Infrastructure department helping to support creating cutting edge pricing programs. You will play a critical role in designing and developing the data solutions needed for research and development as well as providing front line data support in launching new products into market. You will collaborate with multiple stakeholders including data scientists and product analysts to gather requirements, design, and implement robust data solutions.
This role may have in-office requirements depending on candidate location.
This is a ranged posting, level offered will be based on skills and experience at manager discretion.
Responsibilities:- Design, develop, and optimize data pipelines and ETL processes to ensure high-quality data is available for analysis.
Analyze complex datasets to identify trends, patterns, and actionable insights that drive business performance.
Implement data quality checks and governance best practices to ensure data accuracy and reliability.
Utilize python, Spark, and SQL queries to extract, transform, and analyze data from various sources.
Work closely with cross-functional teams to understand their analytical needs and provide tailored solutions that meet business objectives.
Stay current with industry trends, emerging tools, and best practices in data analytics and engineering to continuously enhance analytical capabilities. Qualifications- Strong written and oral communication skills required
Bachelors Degree in Computer Science, Computer Engineering, or related discipline preferred
3-5 years experience in coding for data management, data warehousing, or other data environments, including, but not limited to, working in Python, SQL, ETL, Spark, Snowflake.
About Us
Pay Philosophy: The typical starting salary range for this role is determined by a number of factors including skills, experience, education, certifications and location. The full salary range for this role reflects the competitive labor market value for all employees in these positions across the national market and provides an opportunity to progress as employees grow and develop within the role. Some roles at Liberty Mutual have a corresponding compensation plan which may include commission and/or bonus earnings at rates that vary based on multiple factors set forth in the compensation plan for the role.
At Liberty Mutual, our goal is to create a workplace where everyone feels valued, supported, and can thrive. We build an environment that welcomes a wide range of perspectives and experiences, with inclusion embedded in every aspect of our culture and reflected in everyday interactions. This comes to life through comprehensive benefits, workplace flexibility, professional development opportunities, and a host of opportunities provided through our Employee Resource Groups. Each employee plays a role in creating our inclusive culture, which supports every individual to do their best work. Together, we cultivate a community where everyone can make a meaningful impact for our business, our customers, and the communities we serve.
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 about our benefit offerings please visit: https://www.libertymutualgroup.com/about-lm/careers/benefits
Liberty Mutual is an equal opportunity employer. We will not tolerate discrimination on the basis of race, color, national origin, sex, sexual orientation, gender identity, religion, age, disability, veteran's status, pregnancy, genetic information or on any basis prohibited by federal, state or local law.
Fair Chance Notices - California
Los Angeles Incorporated
Los Angeles Unincorporated
Philadelphia
San Francisco
