Berkley Regional Marketplace (BRM) is a W.R. Berkley Company committed to providing small business customers with the next generation of small business solutions, including offering operational, underwriting and marketing opportunities. Good isn’t good enough for our Berkley Regional Marketplace team. We champion our customers, always seeking a smarter way to provide a more efficient and better user experience.
We are a proud member of W. R. Berkley Corporation, one of the largest commercial lines property casualty insurance holding companies in the United States. With the resources of a large Fortune 500® corporation and the flexibility of a small company, we exclusively work with select independent agents to bring technology solutions that help them build their business.
As a data engineer you will play an integral role in laying the foundation for the creation of a data driven organization. This is a wonderful opportunity to not only use the latest technology, but to help shape the data strategy of a new and growing company. You will work primarily with the data science team, supporting analytics. Additional responsibilities include:
- Play an integral role in laying the foundation for the creation of a data-driven organization.
- Work with Hive to manage, store, and retrieve data. Procure, clean, and store data from external sources.
- Prepare reports, dashboards, and analysis based on data.
- Pull together a variety of data sources for use in analytics.
- Support the business and management with clear and insightful analyses of data.
- Use data science techniques and machine learning models such as scikit-learn package.
- Use Airflow to construct and schedule data pipelines.
- Use big data technologies such as Hadoop and Spark.
- Use Python to access and clean data.
- Leverage knowledge of ETL tools and SQL.
- Master’s degree in computer science, mathematics, statistics, data science, or engineering.
- Three years of experience as a data engineer or software developer.
Must have some work experience with each of the following: SQL Management Studio and Oracle SQL Developer; big data technologies such as Hadoop and Spark; using Python to access and clean data; data science techniques and machine learning models such as scikit-learn package; using airflow to construct and schedule data pipelines; and ETL tools.