MasterClass is looking to expand its data engineering team to support business growth and decision-making processes by designing, building, and operating a scalable data platform.
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.
Responsibilities
- 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.
Other
- Eligible to work in the United States legally
- Strong communication skills, with the ability to initiate and drive projects proactively and accurately
- 4+ years of experience
- Ability to participate in data architecture and engineering decisions
- Ability to build strong cross-functional partnerships with Data Analysts, Product Managers, and Software Engineers
