Have five or more years building data platforms, data pipelines, and data products at scale in a fast-paced environment.
Are an expert developer using SQL and SQL-like query languages. You understand the nuances between the different SQL engines in a big data environment.
You have a strong understanding of different data modelling methodologies (Kimball, Inmon, Data Vault). You understand when to apply the correct modelling techniques to solve different problems on different technologies in our stack.
You are proficient in Python and have experience organizing Python based projects.
Have a proven track record of architecting data systems at scale utilizing the best technology for the job, whether open source, out the box, or homegrown.
You have experience with both proprietary and open source big data technologies and platforms (Snowflake, Vertica, Hive, Spark, Presto, Airflow).
You have worked in a cloud environment (AWS, Azure, GCP).
You have experience defining and creating automated unit and integration testing frameworks for data projects.
You have a functional understanding of different privacy and compliance practices around data (GDPR, CCPA).
You have experience working in cloud infrastructure and can make recommendations when a cloud or vendor-managed service can be utilized.
Understand the basics of the machine learning lifecycle and can build solutions to enable our data scientists to iterate on machine learning applications and ultimately deploy them at scale in productions.
Are detail oriented and extremely organized.
Are experienced working with multiple teams, competing priorities, and geographically distributed stakeholders and partners.
Are focused on business results. You can ruthlessly prioritize and set the proper expectations with partners and stakeholders.