Careers

Sr. Data Engineer at MasterClass
San Francisco, CA, US

MasterClass is transforming online education by enabling anyone in the world to learn from the very best. We are deconstructing what makes an actor able to cry on demand, how an athlete defies gravity, and what it takes to write a bestseller. Our online learning content is available to students anywhere anytime, which supports our mission to democratize education.

We are a rapidly-growing VC-funded startup based in San Francisco. Since our launch in 2015, we have been growing our team, and have created unique online classes taught by famous masters—Gordon Ramsay, Hans Zimmer, deadmau5, Werner Herzog, Shonda Rhimes, Serena Williams, Dustin Hoffman, Jane Goodall, James Patterson, Aaron Sorkin, Annie Leibovitz, Usher, Christina Aguilera, Will Wright, Malcolm Gladwell, and many more to come.

Apply now to find out more about what we are doing behind the scenes.

What we’re looking for:

Data, and how they are used, play a central role at MasterClass and are at the heart of how we make business, product, content, and operational decisions. Our growing Analytics, Data Science, and Data Engineering teams sit at the core of the company and collaborate with a variety of departments to drive decisions and provide direction for future growth at MasterClass. The team tackles challenging problems across many technical disciplines, including time series forecasting, causal inference, optimization, and machine learning. We are looking for an exceptional Senior Data Engineer to help build our data platform to scale the business and enable our Analytics and Data organization in solving those challenges.

Responsibilities of the role:

  • Proactively drive the execution of our data engineering, business intelligence, and data warehouse roadmap
  • Understand and translate business needs into data models to support long-term, scalable, and reliable solutions
  • Create logical and physical data models using best practices to ensure high data quality and reduced redundancy
  • Drive data quality across the organization; develop best practices for standard naming conventions and coding practices to ensure consistency of data models and tracking
  • Define and manage SLA’s for data sets and processes running in production
  • Continuously improve our data infrastructure and stay ahead of technology
  • Design a system for data backup in case of system failure
  • Build strong cross-functional partnerships with Data Scientists, Analysts, Product Managers and Software Engineers to understand data needs and deliver on those needs

Requirements:

  • 4+ years of experience in Data Engineering and Data Warehousing
  • Bachelor's degree in a quantitative field, e.g. Computer Science, Math, Physics
  • Experience scaling data environments with distributed/RT systems and self-serve visualization environments
  • Advanced proficiency with SQL, Perl, Python, Postgres, REST/GraphQL
  • Experience designing and implementing cloud based and SaaS data warehouse (e.g. WS, Hadoop, NoSQL) and developing ETL/ELT pipelines
  • Experience integrating and building data platform in support of BI, Analytics, Data Science, and real-time applications
  • Strong communication skills, with the ability to initiate and drive projects proactively and accurately
  • Work full-time in our San Francisco office
  • Eligible to work in the United States legally

At MasterClass, we believe we put our best work forward when our employees bring together ideas that are diverse in thought. We are proud to be an equal opportunity workplace and are committed to equal employment opportunity regardless of race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or any other characteristic protected by applicable federal, state or local law. In addition, MasterClass will provide reasonable accommodations for qualified individuals with disabilities.  If you have a disability or special need, we would like to know how we can better accommodate you.