Engineering Manager - Ads Data Platform

About the Role

Lead a world-class team dedicated to building and optimizing Reddit's Ads Data Platform, ensuring high performance, reliability, and efficiency for data collection, storage, and analysis at massive scale.

Responsibilities

• Coach, motivate, build, hire, and lead a team of passionate Infrastructure engineers specializing in high-scale data pipelines and storage systems.
• Lead, coordinate, and execute a coherent, ruthlessly prioritized infrastructure roadmap aligned with business needs.
• Set and support a culture of data-informed decision-making, emphasizing efficient processes and strong transparency.
• Facilitate collaboration between product/vertical teams, partner teams, and core platform teams across Reddit.
• Participate in design and coding reviews, ensuring adherence to quality, performance, and best practices.
• Collaborate with cross-functional leads (EMs, PMs, DSs) to translate business requirements into technical directions for the Ads Infrastructure roadmap.

Requirements

• 8+ years of industry experience as a Software Engineer (SWE).
• 3+ years of experience managing engineering teams, including coaching, mentoring, and development.
• 2+ years in a technical lead capacity overseeing systems and architecture design.
• Proficiency in at least two general programming languages such as Python, Go, Scala, Java, or C++.
• Excellent written and verbal communication skills, with proven ability to work effectively with Product Managers, Data Scientists, and other stakeholders.

Nice-to-Haves

• Direct experience managing data-focused engineering teams.
• Prior experience working within the Ads technology domain.
• Experience with Message Queuing Services (e.g., Kafka, SQS).
• Experience with Data Processing Frameworks (e.g., Apache Spark, Apache Flink).
• Experience with Container Orchestration (e.g., Kubernetes).

Role Impact & Focus Areas

• Drive the unification and centralization of data usage patterns across Ads engineering to reduce fragmentation and redundancy.
• Own critical infrastructure components including Spark on Kubernetes, Kafka Connect, Ads Airflow, and the Apache Druid database.
• Focus heavily on optimizing resource usage and driving migration towards more efficient, scalable Ads data infrastructure.