Staff Data Engineer
Job description
About the role
Discord has a highly engaged community of millions of daily active users who use the platform for many different reasons, but there's one thing that nearly everyone does: play video games. Discord plays a uniquely important role in the future of gaming, and we are focused on making it easier and more fun for people to hang out before, during, and after playing games. You will drive technical vision and strategy for our analytical data infrastructure which facilitates the transformation and semantic layer that powers clean, tested, well-documented datasets that the company can trust and self-serve from. The data your team builds 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 Governance, Data Science, Product, Finance, and Engineering teams, and this role reports to the Director of Data Engineering. You will own the design and implementation of data governance programs end to end by partnering with stakeholders and translating policy requirements into flexible and configurable infrastructure in partnership with Data Platform Engineering.
Key facts
What you'll do
Define technical strategy and architectural direction for analytics data infrastructure, building and maintaining enterprise-scale curated datasets and data models.
Own the design and implementation of data governance programs end to end, by partnering with stakeholders and translating policy requirements into flexible and configurable infrastructure in partnership with Data Platform Engineering.
Design and build sophisticated data abstractions 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.
Implement secure and scalable data pipelines that meet the performance, reliability, and compliance requirements of a high-growth platform serving millions of daily active users.
Champion best practices in version control, code review, and CI/CD for data infrastructure to ensure reproducibility and maintainability of analytical assets.
Collaborate with Data Science, Finance, and Product teams to deliver trusted datasets and metrics that inform critical business strategies and external reporting.
Establish and maintain lineage and observability across analytical datasets to support auditing, debugging, and stakeholder confidence.
Define and enforce schema design standards, partitioning strategies, and storage optimization techniques to support efficient querying at scale.
Partner with platform teams to integrate emerging data tools and workflows that improve developer productivity and data reliability.
Contribute to the broader data community within the company by sharing knowledge, patterns, and learnings through documentation and cross-team engagement.
Requirements
7+ years of experience in data and software engineering with a strong focus on building curated, consumer-facing datasets.
7+ years of experience in designing, developing, and maintaining data infrastructure used by data teams at scale.
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.
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.
Ability to thrive in a fast-paced, rapidly evolving environment while maintaining a high bar for data quality and reliability.
Commitment to writing clean, maintainable, and well-tested data code that can be understood and extended by others.
Nice to have
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.
Practical notes
The US base salary range for this full-time position is $279,000 to $310,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.