Senior Reliability Engineer, Data

What you'll do

• Design, build, and manage large-scale distributed data systems on AWS using services like EMR, EKS, and MSK.
• Develop internal tooling and automation frameworks to improve infrastructure reliability, cost-efficiency, and observability.
• Lead initiatives to eliminate toil through automation and scalable deployment patterns.
• Manage cloud-native data platforms to ensure high availability and low latency for petabyte-scale batch and streaming pipelines.
• Perform capacity planning, cost optimization, and incident response for production-critical systems.
• Design and manage Infrastructure as Code using Helm and CRDs to ensure repeatable and secure deployments.
• Contribute to strategic decisions regarding multi-cloud ecosystem adoption and operational excellence.

What we're looking for

• 5+ years of experience in Infrastructure Engineering with a focus on building, scaling, and operating cloud-based distributed data systems.
• Proven expertise running cloud infrastructure built on managed services offered by cloud providers like AWS.
• Strong technical grasp and experience working on Open Source technologies for large-scale data processing, such as Apache Spark, Flink, Kafka, or Iceberg.
• Strong expertise and experience with container orchestration systems like Kubernetes.
• Experience leveraging ML and GenAI capabilities to improve infrastructure and operational efficiency.
• Track record owning reliability and performance of cloud-native data platforms, including capacity planning, cost optimization, and incident response.
• Experience designing, building, and operating large-scale distributed data infrastructure supporting petabyte-scale batch and streaming pipelines.
• Strong programming skills in object-oriented, functional, or procedural languages, preferably Java, Scala, Kotlin, or Python (preferred).