RZR Global Inc.
Senior Data Engineer
San Francisco · Senior
Sponsorship not specifiedDetected 100 days ago
Distributed SystemsCode ReviewKafkaMachine LearningSparkData EngineeringSignal ProcessingLeadershipProblem Solving
About the role
- RZR Global is seeking a talented Data Engineer to join our growing engineering team.
- 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.
Responsibilities
- Architect, 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.
- Drive performance optimization, capacity planning, and cost efficiency across streaming and batch data platforms.
- Conduct design and code reviews, mentor junior engineers, and provide technical leadership across data engineering initiatives.
Requirements
- Required Skills / Experience
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
Nice to have
- Establish and enforce best practices around data quality, monitoring, alerting, testing, and operational readiness.
- 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.
Benefits
- 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.
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