Discord is used by over 200 million people every month for many different reasons, but there’s one thing that nearly everyone does on our platform: play video games. Over 90% of our users play games, spending a combined 1.5 billion hours playing thousands of unique titles on Discord each month. Discord plays a uniquely important role in the future of gaming. We are focused on making it easier and more fun for people to talk and hang out before, during, and after playing games.
Discord is looking for a seasoned technical leader to join our Data team as a Staff Data Engineer, Analytics. You will drive technical vision and strategy for our analytical data infrastructure, owning the transformation and semantic layer that powers clean, tested, well-documented datasets that the company can trust and self-serve from. The data you build won't just inform internal decisions, it will underpin the metrics we share with investors, partners, and the public, requiring exceptional rigor, auditability, and precision. This role works closely with Data Science, Product, Finance, and Engineering teams.
What You'll Be Doing
- Define technical strategy and architectural direction for analytics data infrastructure, building and maintaining enterprise-scale curated datasets and data models
- Own metric definitions end to end, from partnering with stakeholders to define what we measure, to designing and implementing data model in production, to surfacing metrics and dimensions in dashboards and reports
- Design and build sophisticated data models and analytical frameworks using SQL, Python, and modern data stack technologies
- Develop data quality frameworks, monitoring, anomaly detection, and alerting at massive scale, with governance, lineage tracking, and change management rigor appropriate for externally reported numbers
- Drive adoption of consistent data modeling patterns, naming conventions, documentation norms, and metric governance standards across the data organization
- Lead cross-functional technical initiatives across product verticals and mentor engineers to accelerate delivery and harden data systems
- Navigate ambiguity and make sound technical decisions with incomplete information, balancing short-term delivery with long-term infrastructure investment
What you should have
- 7+ years of experience in **analytics or data engineering** with a strong focus on building curated, consumer-facing datasets
- 7+ years of experience in **designing, developing, and maintaining robust data models** from structured and unstructured sources
- Expert-level SQL and strong Python skills, with solid fundamentals in version control and CI/CD
- Proven experience implementing data quality audits, monitoring systems, and automated remediation for massive datasets
- Experience building and owning executive-level dashboards and reports using BI tools (e.g., Looker, Tableau,