Staff Data Engineer, Analytics

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, or similar)
• Strong business acumen and communication skills, comfortable translating ambiguous business questions into concrete metric definitions and explaining complex implementations to audiences from engineering peers to executive leadership
• Track record of hands-on collaboration with Data Science, Finance, and Product teams

Bonus Points

• Passion for Discord or online communities
• Experience building or contributing to a semantic layer or metrics store
• Experience with modern analytics and data engineering tools and workflows (dbt, BigQuery, or similar)
• Experience defining and governing metric standards across a data organization
• Experience with reporting infrastructure subject to external audit or SOX compliance