Staff Data Engineer, Ads

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. Discord seeks a seasoned technical leader to join our Data team as a Staff Data Engineer, focusing on our advertising products.

In this role, you will drive technical vision and strategy for ads data engineering while building and maintaining sophisticated data pipelines, datasets, and analytical tools. You will lead cross-functional initiatives to transform our advertising products through data-driven insights and mentor fellow engineers to deliver exceptional results. This role works heavily with Data Science, Machine Learning, product, sales, and account management teams.

If leading technical innovation, architecting scalable solutions, and empowering teams through data excites you, we encourage you to make a move! What You'll Be Doing Provide technical leadership for Discord's ads data infrastructure - setting architectural direction, establishing engineering standards, and enabling data science, ML, and product teams to build on reliable, well-documented data foundations. Design and own core ads data models : fact/dim tables, canonical datasets, and aggregation layers that power delivery, measurement, targeting, attribution, and ML use cases.

Build and maintain the ML data infrastructure that enables ads ranking, delivery, and targeting - including feature development, label generation workflows, intra-day training dataset construction, and ML input observability to catch data quality issues before they degrade model performance. Build conversion measurement pipelines and integrate third-party attribution data - including Conversion Attribution and Mobile Measurement Partner (MMP) integrations (Adjust, AppsFlyer, Singular) - ensuring attribution accuracy and data parity across measurement surfaces. Design and maintain identity resolution infrastructure and audience pipelines for privacy-compliant targeting and Custom Audiences - with a clear understanding of the governance and regulatory constraints involved.

Build batch and near real-time pipeline infrastructure across the ads ecosystem - pushing toward lower-latency data for ML and reporting use cases on our BigQuery + dbt + Dagster stack.

Requirements

Develop data quality frameworks, monitoring systems, automated anomaly detection, and SLA infrastructure for critical ads pipelines at massive scale. Proactively identify foundational data infrastructure gaps - including those with broad implications across ML, measurement, and reporting - and design scalable, canonical solutions that multiple teams can depend on. Build systems from scratch in a rapidly evolving, greenfield advertising data environment - making sound architectural decisions with incomplete information and balancing short-term delivery with long-term infrastructure investment.

Drive alignment across Data Science, ML Engineering, Ads Product, and GTM teams through clear narratives that connect data infrastructure decisions to business outcomes and revenue impact. Mentor engineers through technical challenges, code and design reviews, and ownership of complex projects - contributing to the culture and engineering standards of the Data Engineering team team. What you should have 7+ years of hands-on experience writing production code and architecting data pipelines with high-volume consumer data in advertising technology domains (ad delivery, ranking, targeting, identity, conversion measurement).