Analytics Engineer

Toronto, CanadaOn-site

Responsibilities

Be the data steward for Consumer products: architect and improve the collection of underlying data while also creating ETLs, reporting dashboards, data aggregations and other deliverables needed for product feature tracking, user retention analysis, A/B testing, and a large number of other data-driven activities.
Develop and maintain robust data pipelines and workflows for data ingestion, processing, and transformation.
Create user-friendly tools and applications for internal use across Data Science and cross-functional teams, streamlining data analysis and reporting processes.
Drive widespread adoption of these tools and applications with a relentless focus on automation, consistency, and reliability.
Lead transformational efforts to build a data-driven culture at Reddit by enabling data self-service.
Proven track record of cross-functional execution and collaboration.

With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information.
On Reddit, people can dive into anything through experiences built around their interests, hobbies, and passions.
Successful candidates have a strong track record of understanding and deeply caring about the purpose of data to support business goals, and can act as an effective conduit between Data Producers and Data Consumers.
Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence. Responsibilities:
Serve as a thought partner for data scientists, engineering managers, and leadership on data foundations, communicating and shaping the data foundations roadmap and strategy for Reddit.
Degree in a quantitative discipline such as statistics, operations research, computer science, applied mathematics, economics, or physics 4+ years of
experience working with large-scale ETL systems (implementation, strategy, and maintenance), building clean, maintainable code and systems (Python preferred) in a production environment.
Strong programming proficiency in Python, SQL, Spark, Scala, etc. •
Experience with data modeling, ETL and ELT concepts, and patterns for efficient data governance.