Senior Data Engineer

Beast Industries is a multifaceted media and entertainment company founded by Jimmy Donaldson, popularly known as MrBeast, the most watched person in the world. Renowned for revolutionizing digital content creation, Beast Industries encompasses a diverse portfolio of ventures that extend far beyond its origins on YouTube. With a mission to entertain, inspire, and create significant social impact, Beast Industries operates across various domains including digital media, philanthropy, consumer products, and innovative business initiatives. At Beast Industries, we believe in the transformative power of digital media and its potential to entertain, educate, and effect positive change. Our commitment to innovation, creativity, and philanthropy drives us to explore new frontiers, create unforgettable experiences, and build a legacy that inspires future generations.

Primary: Bay Area (San Francisco / Peninsula)   |   Secondary: NYC

We're doing an AI-first engineering rebuild for a company that already has an audience of 100M+ people. This is a zero-to-one build with no legacy constraints, so you get to design the data platform from scratch instead of untangling years of pipelines. You're here to build the privacy-safe data foundation that powers everything from product to AI.

You'll design, build, and run the data platform behind the MrBeast ecosystem: the foundation that lets us understand our audience and power great experiences, directly and with partners. That means:

• Build scalable batch and real-time pipelines feeding analytics, reporting, ML, and operational decisions.
• Hit 99.9%+ pipeline availability and cut data delivery latency on critical datasets.
• Build a privacy-safe data foundation that powers AI and product work across the company.

• →Design and implement scalable batch and streaming data pipelines.
• →Develop and maintain enterprise data models, schemas, and storage architectures.
• →Optimize data processing for performance, reliability, and cost.
• →Build automated testing, monitoring, observability, and alerting for data systems.
• →Partner with stakeholders to turn business requirements into technical data solutions.
• →Set and promote data engineering standards, governance, and best practices, and drive adoption.
• →Troubleshoot complex platform issues and production incidents, and mentor engineers through design reviews.

• AI-Native: You're already using AI in your workflow, and you build the data foundations that modern AI and ML actually run on.
• Platform Builder: Typically 8+ years designing and operating production-grade data platforms, with strong data modeling, ETL/ELT, and distributed data processing chops.
• Reliability + Quality Focused: You've driven real improvements in pipeline reliability and data quality, and you can measure and sustain them.
• Independent Leader: You lead complex technical initiatives on your own and take ownership from design through operational support.

Experience building cloud-based data solutions and modern data architectures. Bonus points for supporting ML and AI data workflows, streaming and event-driven architectures, data governance and metadata management, and leading technical communities of practice.