About the Company Our client is the most successful startup you've never heard of.
They've saved 1.5 million Americans $631 million dollars on their medications since they were founded in 2017.
They're focused on making medications more affordable and convenient to purchase and they're giving consumers and their families the power to make better choices and lead healthier lives.
They are a product-forward company that knows how to execute quickly, build things right, and be good to each other while they do it.
About the role We are looking for an experienced Data Engineer to join their remote team.
You need to be a strong problem solver who can act with very little oversight and deliver high quality solutions.
They work in a very challenging business domain, the US HealthCare space.
An important part of the role will be learning this domain and then applying that knowledge to solve complex problems.
The scope of this role is very broad and you will be expected to have an opinion on the approach to data architecture for the entire company.
Responsibilities The main responsibilities include (but are definitely not limited to): Design, build and operationalize large enterprise data solutions using the AWS stack including: S3, Redshift and Kinesis ; Design and build production data pipelines from ingestion to consumption within a big data architecture, using Kinesis, Apache Airflow , Python - Pandas , Golang ; Strategize and implement pricing algorithms which have a direct impact on the bottom line; Responding to ad hoc data analysis requests from the business; Keep the data safe.
They very serious about their customers' personal medical information.
Requirements: 5+ years of software engineering and/or working with Data Solutions Architecting data solutions with complex data sets in the cloud Proficient with cloud data warehousing (Redshift, snowflake etc), Object storage, a relevant data-centric programming language (we use Python - Pandas) Know the difference between simple and easy Excellent communication skills None
