Staff Data Engineer

About the Role

Discord is looking for a Staff Data Engineer to join our Data Engineering team and partner with Consumer Revenue. Our mission is to make it easy for all users to discover, understand, buy, and keep Premium Products on Discord. In this role, you will set technical direction for the data systems that support Nitro, Shop, server monetization and gifting, and other consumer revenue experiences. You will build reliable data foundations that help teams understand performance, run experiments, and make better product and business decisions.

You’ll work closely with Data Science, Product, Finance, Data Platform, and engineering partners.

What You'll Be Doing

• Set technical direction for Consumer Revenue data engineering: identify foundational gaps, define scalable architectures and standards, and lead high-impact initiatives from design through adoption.
• Design and own canonical data models and datasets for consumer monetization, including subscriptions and subscriber states, purchases and payments, Shop, gifting, and Orbs.
• Build and evolve production data pipelines that transform source events and transactional data into accurate, trusted data products across batch and lower-latency processing.
• Partner with cross-functional teams (Data Science, Product, Finance, and Engineering) to define and operationalize key business metrics (subscriber, revenue, booking, retention, usage) ensuring consistency across reporting and experimentation.
• Establish data quality, testing, monitoring, and documentation practices for owned data assets, focusing on accuracy, freshness, auditability, and edge cases.
• Improve self-service analytics by maintaining a discoverable semantic layer, reusable data models, and clear guidance.
• Align on interfaces, data contracts, and operational expectations with upstream Data Platform and downstream Data Science partners.
• Mentor data engineers through design and code reviews, technical guidance, and ownership of complex projects.

What You Should Have

• 7+ years of experience building and operating production data pipelines and data products, including significant hands-on ownership of architecture and implementation.
• Expert-level SQL and strong Python skills, with experience writing maintainable, tested production code.
• A proven track record of designing robust data models from large-scale event, product, or transactional data for analytics, reporting, and experimentation.
• Experience setting technical direction across complex projects and delivering solutions that multiple teams can rely on.
• Strong data quality instincts, including testing, monitoring, data freshness, documentation, and investigating metric discrepancies.
• Experience with modern data engineering tools and workflows (such as dbt, BigQuery, Dagster, or equivalent), version control, and CI/CD practices.
• Experience collaborating with Data Science, Product, Finance, and Engineering to turn ambiguous business questions into clear metric definitions.
• Excellent communication and collaboration skills.

Bonus Points

• Experience with subscription, payments, e-commerce, virtual currency, or consumer monetization data.
• Experience building data products for experimentation, causal measurement, or product launch evaluation.
• Experience developing a semantic layer, metrics store, or self-service analytics platform.
• Experience with streaming or near-real-time data systems, or improving reliability and observability of critical pipelines.
• Experience with AI-assisted analytics tools.
• Passion for Discord, gaming, or online communities.