Millions of people across the world come to Pinterest to find new ideas every day. It's where they get inspiration, dream about new possibilities and plan for what matters most. Our mission is to help those people find their inspiration and create a life they love. As a Pinterest employee, you'll be challenged to take on work that upholds this mission and pushes Pinterest forward. You'll grow as a person and leader in your field, all the while helping users make their lives better in the positive corner of the internet. The Corporate Engineering team is looking for a data engineer with experience configuring, running, and maintaining an enterprise data warehouse. You'll work with our Data Architect to make architecture decisions and implement the infrastructure necessary to support our data warehousing strategy. This will involve building infrastructure to allow data to flow between our engineering and enterprise systems and enable better decision-making throughout our business. The right candidate for this role will have experience in combining open-source and commercial technologies, as well as being comfortable building or buying components to create an enterprise-wide solution. Past cross-functional experience is a plus. This is an internal-customer-facing role, so experience with customer engagement will help!
What you'll do:
Implement our data warehousing strategy for enterprise data at Pinterest; we're just getting started, so there's the opportunity for big impact
Build production-class data pipelines between home-grown and commercial enterprise systems
Work with our Data Architect to make decisions on building vs buying components of the enterprise solution
Establish relationships across Engineering and the business to understand our data landscape, and find sustainable solutions to bridge the gaps
Work with internal customers of the system to find new use cases to support
What we're looking for:
Hands-on experience with a cloud-based data-warehousing system
Hands-on experience with open source big data platforms (Hadoop, Hive, Presto) and familiarity with data visualization (Tableau, D3) technologies
Hands-on experience with commercial ETL tools (e.g., Workato, SnapLogic, Fivetran, or Mulesoft)
Strong skills in Python
Hands-on experience in data modeling, data visualization, and pipeline design & development
Comfortable working across a wide array of technologies, project types, and business requirements.