Senior Data Engineer

MasterClass•San Francisco, CA

18d

About The Position

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. Step into Nas’ recording studio and Gordon Ramsay’s kitchen, and go behind the big screen with James Cameron. Design your career with Elaine Welteroth, get ready to win with Lewis Hamilton, perfect your pitch with Shonda Rhimes and discover your inner negotiator with Chris Voss. 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 plays a central role at MasterClass and is at the heart of how we make business, product, content, and operational decisions. Our Data teams sit at the core of the company, partnering closely with Product, Engineering, Finance, Marketing, and Content to drive insight, direction, and growth. We are seeking a Senior Data Engineer to play a key role in owning, evolving, and scaling our core data platform. This role operates with significant autonomy and influence, partnering closely with Analytics, Product, and Engineering to ensure our data systems are reliable, scalable, cost-efficient, and aligned with how the business operates. You will help shape architectural decisions, raise engineering standards, and ensure our data platform enables analytics, experimentation, and emerging AI-driven use cases.

Requirements

7+ years of experience in Data Engineering, with ownership of production data platforms at scale
Deep expertise designing and operating Airflow, AWS-based data platforms, including Redshift, S3, IAM, and related services in complex production environments
Advanced proficiency in SQL and Python, with strong data modeling and systems design skills
Strong understanding of distributed data processing , modern ELT architectures, analytics workflows and BI use cases, and experience partnering closely with Analytics and business stakeholders.
AI tools knowledge that includes an understanding of prompt engineering and familiarity with modern AI technology stacks
Strong communication skills, with the ability to lead technical discussions, influence architecture, and drive initiatives across teams

Responsibilities

Design, build, and operate robust, fault-tolerant, and observable data pipelines using Airflow and modern ELT best practices
Architect, enhance and improve data ingestion, AWS data infrastructure, including Redshift, S3 and monitoring
Partner with Analytics, Product, Finance, Marketing, and Content teams to design canonical, analytics-ready datasets that power key metrics such as growth, engagement, retention, and revenue
Define, implement, and enforce SLAs, data quality checks, observability, and alerting for production data systems.
Take shared ownership of data platform reliability, participating in on-call rotations and driving root-cause fixes for incidents
Contribute to design reviews, raising engineering quality, and sharing best practices
Evaluate and introduce data tooling that improves reliability, developer productivity, and analytics velocity
Collaborate deeply with cross functional teams to align event design, source systems, and data contracts