Data Engineer

Who We Are

MasterClass is the streaming platform where the world’s best come together so anyone, anywhere, can access and be inspired by their knowledge and stories. We put you in the room with the creators, thinkers, makers, and leaders who have changed the world, so that you can change yours. Members get unprecedented access to 150+ instructors and classes across a wide variety of fields, including Arts & Entertainment, Business, Design & Style, Sports & Gaming, Writing, and more. It's a pivotal time for MasterClass – and we want you to be a part of the journey. With offices in San Francisco (HQ) and Waterloo, Ontario, plus a studio in Los Angeles, we are looking to expand our team to support the business. If you want to help make an impact on our members' lives – we want to hear from you!

Summary of The Role

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. At MasterClass, data is pivotal to our decision-making processes, influencing business strategies, product development, content creation, and operational efficiency. Our growing Data teams sit at the core of the company and collaborate with various departments to drive decisions and provide direction for future growth at MasterClass. Our expanding Data teams are central to the company, collaborating across multiple departments to drive decisions and steer future growth at MasterClass. Our Data engineering team tackles challenging problems across many technical disciplines, including data warehouse, cloud infrastructure, data orchestration systems, critical integrations, and more. We seek an exceptional Data Engineer to help design, build, and operate our data platform to scale the business and enable the Data organization and teams to solve challenges.

What You Will Do

• Design, build, and manage our data warehouse, data storage, and data ingestion solutions.
• Implement robust and fault-tolerant systems for data ingestion and processing.
• Develop canonical datasets to track key product metrics, including user growth, engagement, and revenue.
• Understand and translate business needs into data models to support long-term, scalable, and reliable data pipelines.
• Enhance and maintain the Data Infrastructure using best practices and latest features to ensure high data quality.
• Define and manage SLA’s for data sets and processes running in production.
• Continuously improve our data infrastructure and empower teams with the best data tooling and systems.
• Build strong cross-functional partnerships with Data Analysts, Product Managers, and Software Engineers to understand data needs and deliver on those needs.
• Participate in data architecture and engineering decisions, leveraging your strong experience and knowledge.
• Build lineage and auditability into data pipelines.
• Be part of a data engineering team that is also responsible for the reliability of the data systems that are built and be available to respond to critical incidents as needed.
• Ensure the security, integrity, and compliance of data in accordance with industry and company standards.

About You (Requirements)

• 4+ years of experience in Data Engineering and Data Warehousing.
• Experience scaling data environments with distributed processing technologies and frameworks.
• Advanced proficiency with SQL, Python, Postgres, and integrations via APIs.
• Experience working in an AWS cloud environment in designing and implementing cloud data warehouses, other types of storage, and developing ETL/ELT pipelines.
• Experience integrating and building a data platform in support of BI, Analytics, and Data Science.
• Expertise with ETL schedulers such as Airflow, Dagster, Prefect, or similar frameworks.
• AI tools knowledge that includes an understanding of prompt engineering and how data impacts LLM performance in RAG pipelines; familiarity with modern AI technology stacks; ensuring high-quality data inputs for AI models; and integrating AI capabilities into business intelligence solutions.
• Strong communication skills, with the ability to initiate and drive projects proactively and accurately.
• Eligible to work in the United States legally.

Key skills/competency

• Data Engineering
• Data Warehousing
• SQL
• Python
• AWS
• ETL/ELT
• Data Pipelines
• Cloud Infrastructure
• AI Tools
• Data Governance