Manager – Data Foundations

8+ years of software development experience in the data platform and datastores disciplines.
Familiarity with the inner workings of a data pipeline, understand the difference between streaming and batch processing data pipelines, and understand how a database engine builds a query plan.
Demonstrable experience in operating and supporting infrastructure within a cloud environment like AWS.
Direct, hands-on experience in operating and managing a highly available datastore in production cloud environments (preferably AWS), such as PostgreSQL or MySQL, DynamoDB, Elasticache, or Kafka.
An understanding of the tradeoffs between data encryption and tokenization mechanisms, and how to manage the performance tradeoffs between them.
Prior experience managing and growing individual contributors.
Experience with Python or Scala (or comparable high-level language) and experience working on large distributed systems and frameworks like Spark / Flink for data pipelines.
The ability to identify strength and weakness of individuals in order to maximize team effectiveness and provide guidance to individuals when needed for coaching or mentoring.
The ability and experience to mediate between competing product and technical priorities and align priorities and goals through collaboration with technical leads and product managers.

Staff and manage a team of engineers responsible for the Data Foundations, from data ingestion and routing, and meet all SLOs and SLAs for the products your team owns.
Be focused on eliminating toil within your team and your own customers through self-service tooling, and internally developed and published libraries for all the products you own.
Represent the Data Foundations team in internal customer meetings, cross functional workstreams, maintain roadmaps for the team, help prioritize customer requests and drive iterative delivery of projects enabling our stakeholders to be successful.
Establish team level performance indicators to measure efficiency of the team’s output and impact to the Team Members we support.
Inspire a healthy, collaborative, empathetic engineering culture in line with Peloton’s values, helping your team develop and grow along the engineering journey at Peloton.
Ensure that data pipelines are implemented with quality and observability included, along with appropriate encryption and tokenization techniques.
Partner closely with our security teams, ensuring logging and auditing mechanisms are in place and responding to any security incidents around the data infrastructure your teams support.
Champion engineering and operational excellence, drive database reliability and incident management by establishing metrics and processes for assessment and improvements.

Familiarity with orchestration tools like Kubernetes, and data orchestration services like Glue, Data Lake Formations, and Airflow is a plus.