Senior Data Engineer

Jerry - Los Angeles, CA

Full-time - Mid Level

Los Angeles, CA

101-250 employees

Sporting Goods, Hobby, Musical Instrument, Book, and Miscellaneous Retailers

About the position

As a Senior Data Engineer at Jerry, you will play a crucial role in building and optimizing the data infrastructure that supports the company's mission to create the first AllCar super app. This position involves collaborating with data scientists, software engineers, and various stakeholders to develop data pipelines that ensure data availability and accuracy, ultimately driving business growth. You will leverage your extensive experience in data engineering to lead the development of scalable infrastructure solutions that can support significant company growth.

Responsibilities

• Partner with data scientists, software engineers, and cross-functional stakeholders to build data pipelines that provide critical data and insights.
• Collaborate with data scientists and machine learning engineers to evolve, optimize, and integrate predictive models.
• Work with software engineers and data scientists to build data pipelines for application data consumption and refinement.
• Define data engineering standards and best practices, driving operational excellence.
• Perform regular maintenance and optimization of data infrastructure.

Requirements

• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical discipline; Master's degree preferred.
• 5+ years of experience in data engineering or a similar role.
• Proven success in communication with database users, software engineers, and senior management to collect requirements and define data engineering strategies.
• Outstanding communication and problem-solving skills.
• Experience with data modeling, data warehousing, and ETL pipeline development.
• Experience with column-based databases (e.g., Amazon Redshift, ClickHouse) and analytical platforms (e.g., Tableau, Qlik, Power BI).
• Hands-on experience and advanced knowledge of SQL.
• Experience with big data technologies (e.g., Spark, Clickhouse, Redshift, Snowflake).
• Experience in process automation and deployment of advanced machine learning models.