The Athletic is a digital sports media company that brings true sports fans closer to the athletes, teams and leagues that captivate their attention. We serve a multi-faceted audience that craves a richer connection and understanding with immersive storytelling and a like-minded community of fans. Founded in 2016 and with major operational hubs in San Francisco, Los Angeles, London and Melbourne, we empower a truly global team of more than 600 creators and cover more than 250 professional sports and collegiate teams across the United States, Canada and the UK. Our newsroom has produced thousands of in-depth reports along with more than 120 podcasts and other forms of premium content. Put simply, The Athletic is at the center of a sports fan’s universe.

Our small but mighty Data Engineering Team owns all data infrastructure for The Athletic: MySQL production database, analytics data streaming pipeline using Kubernetes, Kafka, EMR (Spark), S3, Airflow and Redshift, all hosted in AWS. The team works on many different things: scaling our data infrastructure, modeling, recommendations, product features, data visualization - it’s never boring! We have lots of exciting things we want to build and we don't have enough time to build them. That's where you come in! 

You'll be leading a team of 3 data engineers using cutting edge technology to build and deploy the tools and data infrastructure that power our platform. You should be interested in building systems for scale, performance, and reliability. We all wear a lot of hats, so you’ll have the opportunity to work on database administration, infrastructure, ETL, microservice and model deployment, testing, experiments, and more depending on your interests.  We’re a team of generalists interested in continuously learning new areas and we’ll expect you to be one as well. Our team is always experimenting and we trust and encourage our engineers to dream up and try out their own ideas and features.

Responsibilities

• Lead a team of data engineers and work closely with our data science and data analytics teams. Architect solutions, provide mentorship, give guidance.
• Partner with Product and Engineering teams to build and deploy features backed by machine learning and modern data toolsets.
• Inform, influence, support, and execute our product decisions.
• Build/maintain monitoring systems, dashboards, and metrics to manage and maintain visibility into the performance of our data pipelines and products.
• Mine massive amounts of data and extract useful product insights.
• Manage development of data resources, gather requirements, organize sources, and support product launches.

Requirements

• Bachelor’s Degree in Computer Science, Math, Physics, Engineering, or related quantitative field.
• 5+ years data engineering experience.
• 2+ years of experience in leading or managing a team.
• 2+ years of experience with Python, SQL or other programming languages.
• 2+ years of experience with Docker, AWS, or similar environment.
• Experience initiating and driving projects to completion with minimal guidance.
• Experience communicating the results of analysis.

Nice to Have

• Experience with Kafka, Kubernetes, Redshift and Spark.
• Experience with large data sets and distributed computing (Hive/Hadoop).