Site Reliability Engineer - Data Platform

Requirements:

• Strong experience managing distributed data platforms (e.g. Kafka, Hadoop, Spark, Dremio); including full installation, debugging and performance tuning
• Hands on experience deploying, configuring and orchestrating software on Linux and Kubernetes, with proven ability to troubleshoot issues in both environments
• Strong experience with infrastructure as code (Ansible preferred) and best practices
• Proficient programming experience in Python
• Ability to read, write and tune SQL queries
• Comfortable reading Java source code, tuning and debugging running JVMs
• Familiarity with data lakehouse technologies (e.g. Iceberg or Delta Lake) as well as query engine technologies (e.g. Dremio, Presto or Trino)
• Exposure to workflow orchestration tools like Airflow or Dagster
• A proactive mindset: you're not just fixing issues but preventing them
• Comfortable working across teams, with minimal oversight

What You'll Be Doing:

• Design, implement and operate our data platforms
• Improve observability so we catch issues before our users do
• Build automation to reduce toil and allow our systems to scale
• Support and own reliability of critical services (e.g. HDFS, Kafka and Dremio)
• Drive long-term architectural improvements, not just fixing issues, but preventing them

Perks and Benefits:

• Data Tools: Hadoop (HDFS), Kafka, Dremio, Iceberg, Clickhouse, Spark, Airflow, Flink
• Infrastructure Automation: Ansible, Puppet, Kubernetes (ArgoCD, Helm, Kustomize)
• Observability: Prometheus, Grafana, AlertManager
• Scripting: Python, Bash, SQL
• Others: PCAP infrastructure