Now more than ever, the Internet is a utility that facilitates modern life. At Mozilla, we take this to heart, striving to build products that keep the Internet open, accessible, and secure for everyone. We handle terabytes of data every day from millions of users to guide our decision-making processes. We need your help to enable the future of Mozilla in a way that makes us proud!

The Analytics Engineering team at Mozilla is on a mission to empower all Mozillians to make data informed decisions by ensuring they have access to the data they need to do their jobs, in the appropriate format, when they need it and regardless of their data skill level. As an Analytics Data Engineer at Mozilla, you’ll be working closely with other Data Engineers and Data Scientists to build out analytics datasets that help our users better understand the business. You will:

• Help model analytics datasets that enable efficient reporting of different business activities / processes.
• Help design and build systems to monitor and analyze data from Mozilla’s products to ensure the quality, reliability and integrity of our business critical data.
• Help design, build, and improve the infrastructure for ingesting, storing, and transforming data at a scale of tens of terabytes per day.
• Work with data scientists to answer questions and guide product decisions.

General Professional Requirements:

• Proficiency with SQL and Python

• Software engineering fundamentals: modularity, abstraction, data structures, and algorithms.

• Ability to work collaboratively with a distributed team.

Specific Skills/Experience:

Our team requires skills in a variety of domains. You should have proficiency in one or more of the areas listed below, and be interested in learning about the others.

• You have experience with data infrastructure: databases, message queues, batch or stream processing
• You have experience preparing and optimizing data for use in a BI tool such as Looker (preferred), Tableau, Power BI or other similar tools
• You enjoy performing analysis and have used data to answer specific questions and guide company decisions. This role requires exploratory data analysis to help inform what we build for the rest of the organization for them to be able to conduct analysis efficiently on their own.
• You have experience building modular and reusable ETL/ELT pipelines in distributed databases/cloud data warehouses such as BigQuery, Redshift or Snowflake.
• You have experience with highly scalable distributed systems hosted on cloud providers (e.g. Google Cloud Platform)