Data Engineer

ABOUT THE ROLE

Peloton is looking for a talented Data Engineer to join the Data Science team. In this role, you will help scale Peloton’s data infrastructure for business needs by building batch and streaming data pipelines that process terabytes of data daily. You will have the opportunity to work with multiple teams of engineers and business partners to support analytics and reporting data needs across the organization.

This role will be hybrid, not remote.

YOUR DAILY IMPACT AT PELOTON

• Build and maintain data pipelines to support the data and analytics needs of different stakeholders across multiple business verticals including Supply Chain, Logistics, Finance, Marketing, Product, etc.
• Understand end to end data interactions and dependencies across complex data pipelines and data transformation and how they impact business decisions.
• Collaborate with the team to develop best practices in building our next generation data platform.
• Implement data lake ingestion pipelines using Apache Spark and Apache Hudi.

YOU BRING TO PELOTON

• 3+ years in data engineering roles or 4+ years in data-intensive engineering or software development roles.
• Bachelor’s degree in a STEM related field. Advanced degree preferred.
• Strong knowledge of at least one programming language: Python (preferred) or Java.
• Working knowledge of developing ETL/ELT pipelines, including data processing and transforming data to meet business goals.
• 1+ years of experience with big data architectures and tools to efficiently process large volumes of data.
• Familiar with REST for accessing cloud based services.
• Excellent knowledge about databases or data warehouses, such as PostgreSQL or Redshift.
• Strong understanding and working knowledge of using SQL (PostgreSQL or Redshift preferred) for various reporting and transformation needs.
• Comfortable with Linux operating system and command line tools such as Bash.
• Team player with excellent communication, adaptability and collaboration skills.
• Experience running Agile methodology and applying SCRUM to data engineering.
• Experience with GIT and Github.

BONUS POINTS IF YOU HAVE

• Experience working in a cloud-based ecosystem, preferably AWS (including RDS, Redshift, Athena, Glue, etc.).
• Experience with Apache Hadoop, Hive, Spark or PySpark.
• Experience with orchestration tools such as Apache Airflow.
• Experience with data integration tools such as Airbyte.

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