Sr. Data Engineer, App

About Us

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.

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. You're not here to maintain someone else's pipelines. You're here to build the data infrastructure that powers every product decision we make, from real-time telemetry that keeps our systems healthy to the analytics pipelines that tell us what our users actually want.

The Product

You'll own the event and data infrastructure that sits beneath everything: the pipelines, platforms, and tooling that turn raw user behavior into reliable, decision-ready data. The work spans consumer products, media, gaming, and e-commerce, all sitting on top of a large and fast-growing user base. That means:

Operational telemetry that keeps the platform healthy and a separate, well-designed analytics layer that powers product and business decisions.

A data platform that supports real-time monitoring, long-term metric tracking, and the experimentation infrastructure that every product iteration depends on.

Event pipelines that handle high-volume user events with the right instrumentation contracts, schema validation, deduplication, late-arriving event handling, and identity stitching.

What You'll Do

• Own, build, and operate the telemetry data pipeline that powers SRE and operational monitoring, ensuring real-time data freshness, reliability, and observability across all production systems.
• Own, build, and operate the analytics data pipeline that supports product and user experience analysis, including event instrumentation, schema design, data quality checks, deduplication, late-arriving event handling, and identity stitching at scale.
• Partner with data science, product, and SRE stakeholders to translate requirements into pipeline design, including cases where the requirements are vague and need to be shaped before implementation.
• Embed AI tooling into the data engineering workflow to accelerate pipeline development, data quality monitoring, and insight delivery.
• Who You Are
• AI-Native: You're already using AI tools daily to move faster, from writing pipeline code to diagnosing data quality issues.
• Data Platform Builder: 5+ years building and operating production data pipelines for high-volume consumer products, with hands-on experience in event instrumentation, schema design, and data quality at scale.
• Business Connected: You don't wait for a data scientist to tell you what the pipeline should do. You understand the product well enough to translate vague requirements into robust pipeline design, and you can tell the difference between what someone asked for and what they actually need.
• Operational and Analytical Thinker: You understand that operational telemetry and analytics serve different purposes and require different approaches, and you design accordingly.
• Strong experience with streaming and batch data pipelines, event-driven architectures, and at least one major cloud data stack (AWS, GCP, Databricks, Snowflake, or equivalent). Bonus points for experience in consumer products, media, gaming, or ads, familiarity with sessionization and identity stitching at scale, and prior work alongside data science or product analytics teams.
• Compensation: $178,000 –$223,000 base + equity + benefits
• Hybrid Model: Expected ~3 days per week in-office (San Mateo, CA)