About the Team
At GOAT Group, the Engineering team is an integral part of our dynamic company. By joining the team, your skills will be front and center, working alongside other passionate individuals to solve problems and build software. From launching compelling new consumer experiences, tackling global logistics challenges to scaling infrastructure to facilitate our rapid growth technology is essential to driving our vision forward. The work you do will change the way the world shops, while also empowering entrepreneurs, including individual sellers, brands and boutiques.
Role Overview
The Data Engineering team is responsible for building and maintaining data solutions that deliver value to our internal and external stakeholders. We are part of the Data Platform team here at GOAT and work closely with Data Scientists, Data Analysts, and the broader Engineering team to deliver data needs. We are looking to add an innovative engineer with a strong sense of ownership, who is able to work both independently and as part of a team.
In this role, you will:
Lead architectural designs and build reliable data pipelines that move data at scale
Collaborate with internal stakeholders to deliver data needs that drive critical business decisions at GOAT
Optimize data storage and data modeling for efficient data retrieval and transformation across large datasets
Move essential data pipelines from batch to real-time setup
Address process improvements, automate manual processes, and drive changes to stay close with big data advancements
We are looking for:
5+ years of industry experience
Proficiency with SQL and Python or Go
Proficiency in data warehousing and data modeling
Proficiency building batch and real-time data pipelines in production
Experience with data orchestration tools like Airflow or Luigi
Experience with AWS or another cloud platform
Bonus if you have experience with streaming tools: Kafka, Flink, and Materialize or similar
Bonus if you have experience with data compliance regulations such as GDPR and CCPA
Bonus if you have experience monitoring for data quality and integrityBonus if you are familiar with Data Visualization tools like Mode, Looker, or Tableau
GOAT is the global platform for the greatest products from the past, present and future. Since its founding in 2015, GOAT has become the leading and most trusted sneaker marketplace in the world. Through its unique positioning between the primary and resale markets, the company offers styles across various time periods on its digital platforms and in its retail locations, while delivering products to over 30 million members across 170 countries.
Established in New York City over 15 years ago, Flight Club revolutionized sneaker retail as the original consignment store for rare shoes. Carrying the rarest exclusives and collectible sneakers, Flight Club has evolved from a one-stop sneaker destination, to a cultural hub for sneaker enthusiasts and novices alike. With three brick-and-mortar locations in New York City, Los Angeles and Miami, Flight Club remains the premier source for authentic, rare sneakers.
The company is backed by strategic investor Foot Locker, Inc. as well as some of the leading names in venture capital including D1 Capital Partners, Accel, Andreessen Horowitz, Index Ventures, Matrix Partners, Upfront Ventures, Webb Investment Network and Y Combinator.
We encourage you to apply even if you feel unsure about whether you meet every single requirement. We look for people who are passionate about what we do, not just those who check off all the boxes.
GOAT Group will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, if applicable. If you are a California resident, please review our California Privacy Rights Notice for Job Applicants.
If you are an EU or UK resident, please review our EU / UK Candidate & Employee Privacy Notice.
Associated topics: data administrator, data analyst, data analytic, data engineer, data scientist, database, etl, sql, sybase, teradata