Data Engineer
SF, NY, Toronto, Portland, or remote
Full-time
Mercury
In the 1880s, Herman Hollerith noticed the US Census was taking over 8 years to calculate. To solve this, he invented a tabulating machine using punch cards that dramatically sped up the process and served as the foundation for innovation in high quality data gathering.
We’re looking for our first Data Engineer who can help us build our high quality data engine that informs how we invest in and build Mercury’s future. You’ll be early to building a data-informed culture across Mercury so that we can all determine what’s happening, react quickly, and invest intelligently.
Here are some things you’ll do on the job:
- Partner with leadership, engineers, and data scientists to understand data needs and build systems that deliver high quality and reliable data.
- Own and maintain the data systems that extract, transform, and load data into internal and external tooling.
- Apply proven expertise and build high-performance scalable data warehouses.
- Design, build, and launch efficient & reliable data pipelines to move and transform data (both large and small amounts).
- Design and develop new systems in partnership with software engineers to enable quick and easy consumption of data.
You should:
- Have 2+ years of experience working with analytics teams on building high quality and reliable data infrastructure.
- Be able to navigate from architecture and implementation decisions related to data infrastructure to guide teams towards building reliable and accurate pipelines and company-critical data sets.
- Have familiarity with postgres backend data, Snowflake, and data transformation tools like dbt.
- Value quality in data tools, testing, and innovation.
About the team
Engineers at Mercury have extensive influence on product. We like correctness, cross-functional communication, and Monopoly Deal.
