Who are we?
RZR Global is an AI-driven company specializing in mobile advertising solutions designed to fuel revenue growth. We leverage AI to discover audiences in a privacy-first environment through trillions of contextual bidding signals and proprietary behavioral models. Our audience engagement platform includes creative strategy and execution. We handle 5 million mobile ad requests per second from over 10 billion devices, driving performance for both publishers and brands. We are headquartered in San Francisco, CA, with a global presence across the United States, EMEA, and APAC.
RZR Global is seeking a talented Data Engineer to join our growing engineering team. This role is ideal for an engineer with a strong background in building and operating large-scale, high-performance data pipelines. As a Data Engineer, you will design, develop, and maintain the data infrastructure that powers our programmatic Demand-Side Platform (DSP), enabling real-time and batch processing of massive volumes of event, log, and campaign data. You will work with technologies such as ClickHouse, Kafka, Spark, HDFS, and Fluentd to ensure data is reliable, scalable, and accessible for analytics, reporting, and machine learning. You will collaborate closely with backend engineers, data scientists, and product teams to deliver high-quality data solutions that support real-time bidding (RTB), optimization, and business insights.
Key ResponsibilitiesArchitect, design, and own highly scalable, fault-tolerant data pipelines for real-time and batch processing of large-scale event and campaign data.
Lead the development of data processing systems using Kafka, Spark, ClickHouse, HDFS, and Fluentd, with a strong focus on performance, reliability, and data correctness.
Partner closely with backend engineers, data scientists, and product teams to define data models, SLAs, and end-to-end data flows that support real-time bidding (RTB), analytics, and machine learning use cases.
Drive performance optimization, capacity planning, and cost efficiency across streaming and batch data platforms.
Establish and enforce best practices around data quality, monitoring, alerting, testing, and operational readiness.
Conduct design and code reviews, mentor junior engineers, and provide technical leadership across data engineering initiatives.
Evaluate and introduce new data technologies, frameworks, and architectural improvements to evolve the data platform at scale.
6+ years of experience in data engineering, backend engineering, or distributed systems development.
Strong proficiency in building and operating large-scale data pipelines using technologies such as Kafka, Spark, ClickHouse, HDFS, and Fluentd.
Solid understanding of distributed systems concepts, including data partitioning, fault tolerance, consistency, and scalability.
Experience designing efficient data models and schemas for analytical and real-time workloads.
Strong experience with streaming and batch processing architectures.
Experience with performance tuning, capacity planning, and troubleshooting production data systems.
Familiarity with data quality, monitoring, alerting, and operational best practices.
Knowledge of real-time systems, ad tech, programmatic advertising, RTB, or large-scale analytics platforms is a plus.
Excellent problem-solving skills, strong ownership mindset, and ability to operate effectively in a fast-paced, high-scale environment.
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
Skills Required
- 6+ years of experience in data engineering, backend engineering, or distributed systems development.
- Experience building and operating large-scale data pipelines using Kafka, Spark, ClickHouse, HDFS, and Fluentd.
- Solid understanding of distributed systems concepts, including data partitioning, fault tolerance, consistency, and scalability.
- Experience designing efficient data models and schemas for analytical and real-time workloads.
- Strong experience with streaming and batch processing architectures.
- Experience with performance tuning, capacity planning, and troubleshooting production data systems.
- Familiarity with data quality, monitoring, alerting, and operational best practices.
- Knowledge of real-time systems, ad tech, programmatic advertising, or RTB.
- Excellent problem-solving skills and strong ownership mindset.
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
RZR Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about RZR and has not been reviewed or approved by RZR.
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Flexible Benefits — Job listings and company descriptions highlight remote-friendly or flexible work arrangements across global offices, suggesting adaptability in how benefits are delivered across locations.
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Pay Growth & Progression — Technical and specialized roles are portrayed as competitively paid relative to local markets, indicating opportunities for solid compensation in higher-skill positions.
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Healthcare Strength — Employer-provided health and welfare benefits are referenced, implying access to standard medical coverage even if specific plan details are not publicly disclosed.
RZR Insights
What We Do
RZR powers performance for the world's most ambitious brands through proprietary neural architecture that optimizes across user acquisition, retargeting, CTV, and influencer campaigns as one connected performance system. With four owned-and-operated data centers that process 6M+ queries per second, RZR turns signals into strategy and impressions into impact. Trusted by brands across gaming, consumer, food and beverage, retail, and entertainment. Built on over a decade of performance data and backed by AI and ML experts and industry veterans across offices in San Francisco, New York, London, Bangalore, Beijing, Manila, and Seoul. RZR delivers retention-led growth intelligence: faster, sharper, and built for performance at scale.
