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 Management team under the Data Platform department is to play a leadership role in enabling teams to catalog, trace, discover and consume trusted golden datasets in a secure manner. 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 Management team under the Data Platform department to own and provide technical expertise and leadership around federated data governance, discovery and lineage. As a part of the Data Management team, you will be working across a wide range of problems in the data catalog, discovery, lineage and privacy space. Some of the few challenges you will work on in your first year are: How do we catalog and provide discoverability of all datasets including golden datasets available across the company? How do we categorize and certify a golden dataset as meeting the quality standards? How do we build a lineage graph of datasets? How do ensure that PII datasets meet compliance requirements? How do we build an access control layer on top of our data lake to enable decentralized teams to share their data?

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 key technical leader and owner of multiple workstreams under Data Management viz. Business Continuity & Disaster Recovery, Cost Optimization, Data Cataloging & Metadata Management, Data Discovery, Data Lineage, Data Privacy & Compliance, Data Security & Access Control
• Represent the data management team where deep knowledge of our data management stack is needed - Working Groups, cross-functional work streams and Special Interest Groups
• Focus on metadata management, data lake standards and access controls around it, ensuring that quality and well-trusted golden datasets are discoverable and addressable.
• Review code and provide feedback to ensure it is high quality, efficient, well-tested and documented.
• 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 management, data lakes and data catalogs
• You have experience in a cloud environment like AWS and familiarity with tools like Glue Catalog and Data Lake Formation.
• You are passionate about privacy, data lakes, catalogs, metadata management,  data security and cost optimization
• You have experience building out data lakes and data catalogs.
• Proven experience working with rapid product development in an agile environment is preferred
• You are pragmatic without compromising on software quality and standards.