Open to hire New York, NY - Bay Area, CA - Remote, USA

The Opportunity

At Peloton, we treat Data as Product - a valuable asset and a critical piece of our decision making process. The mission of the Data Engineering team under the Data Platform department is to be an enabler and force multiplier that empower and enable teams to produce operational and analytic datasets and expose product datasets. Our core guiding principles are 1) enable data as a product 2) ensure data reliability and 3) optimize for data productivity.  

We are looking for a Staff Engineer to join our Data Engineering team under the Data Platform department  to own and provide technical expertise and leadership around data engineering. As a part of the Data Engineering team, you will be an enabler working on decentralized stream enabled teams to unlock their ability to use core data infrastructure and to promote best practices and data standards. 

You Will

• Adopt and evangelize data mesh principles and event-driven architecture across decentralized product teams and promote the principle of data as a product.
• Be a subject matter expert on data modeling, data pipelines, data quality and data warehousing.
• Enable decentralized teams to build their data pipelines and expose golden datasets.
• Ensure that data pipelines are implemented with quality and observability included. 
• Partner with engineering teams and the data infrastructure team building and providing feedback on the data tools being built.
• Coach and mentor engineers across the engineering team to build a data culture.

You Have

• You have 10+ years of experience in engineering especially data engineering
• You have experience in a cloud environment like AWS and familiarity with tools like Kubernetes, Kafka, Airflow, Glue, Athena and Data Lake Formation.
• You are passionate about event-driven architecture, microservices , data reliability and quality. You have experience with Python or Scala and experience working on large distributed systems and frameworks like Spark/ Flink.
• Proven experience working with rapid product development in an agile environment is preferred
• You are pragmatic without compromising on software quality and standards.