Staff Data Engineer, Ads

What You'll Be Doing

• Create and maintain complex, enterprise-scale data pipelines and foundational datasets while defining technical strategy and architectural direction for advertising products
• Design and build sophisticated ETL processes, data models, and analytical frameworks using SQL, Python, and modern data stack technologies
• Build and maintain the data infrastructure that powers Ads ML - feature pipelines, label generation workflows, and training data systems that enable our ranking and delivery models
• Develop data quality frameworks, monitoring systems, automated anomaly detection, and alerting infrastructure that operates at massive scale
• Collaborate with data scientists, ML engineers, and product teams to identify high-impact data infrastructure opportunities, owning design through implementation
• Drive cross-functional technical initiatives solving sophisticated data engineering challenges
• Build scalable rubrics that help lead and mentor engineers through projects that accelerate launch velocity 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 hands-on experience writing production code and architecting data pipelines with high-volume consumer data in advertising technology domains (eg. ad delivery, ranking, targeting, identity)
• 7+ years of direct implementation experience designing, coding, and maintaining complex data models and systems handling structured and unstructured data sources
• Expert-level coding abilities in SQL, Python, and modern data engineering frameworks with demonstrated ability to write performant, maintainable, and scalable code
• Digital advertising data engineering expertise with hands-on experience building high-throughput data pipelines for ad serving, conversion tracking, advertising measurement, or integrating and normalizing third-party advertising data from external platforms and partners
• Proven hands-on experience implementing and debugging data quality audits, monitoring systems, and automated remediation for massive datasets (billions+ rows)
• Strong technical communication abilities to explain complex implementations to stakeholders while thriving in rapidly-evolving technical environments
• Passion for solving complex problems through direct technical contribution and desire to work with exceptional engineers on challenging data infrastructure
• Hands-on collaboration experience implementing solutions with data science, ML engineering, and product teams through direct technical contribution
• Collaborative mindset with intellectual curiosity and commitment to technical excellence through hands-on delivery

Bonus Points

• Passion for Discord or gaming in general
• Hands-on integration experience implementing connections with external data sources, APIs, and third-party advertising platforms
• Experience with modern data storage and processing technologies (BigQuery SQL, Airflow, Dagster, DBT, or similar)
• Experience with data visualization and dashboarding technologies (Looker, Tableau, or similar)
• Experience with designing data architecture to power a variety of use cases, including experimentation

The US base salary range for this full-time position is $248,000 to $279,000 + 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.