Big Data DevOps Engineer (Hadoop / Cassandra)
On-site 4 days a week \| Toronto, ON
Overview:
We’re looking for a DevOps Engineer with strong expertise in big data platforms, specifically Hadoop and/or Cassandra (both is a plus). This role requires proven experience administering, configuring, and troubleshooting large-scale distributed systems, as well as deep Linux administration and DevOps toolchain skills. Candidates must demonstrate hands-on engineering experience, not just surface-level administration.
Key Responsibilities:
Install, configure, and maintain Hadoop or Cassandra clusters in production environments.
Manage and optimize performance, replication, failover, and disaster recovery for big data systems.
Develop and maintain automation scripts (Bash, Python, PowerShell) for deployment and monitoring.
Build and manage CI/CD pipelines (Jenkins, GitHub/Bitbucket, Nexus).
Automate provisioning using Terraform, Ansible, Salt, or similar.
Deploy and manage cloud infrastructure (Azure preferred; AWS/GCP a plus).
Monitor and log systems using tools like Splunk, DataDog, ELK, etc.
Ensure data security, scalability, and availability across environments.
Must-Have Skills:
5-10 years of DevOps / Systems Engineering experience.
Strong Linux administration background (Red Hat preferred).
Hands-on experience with Hadoop or Cassandra (administration, scaling, troubleshooting).
Scripting skills (Bash, Python, PowerShell).
Experience with cloud platforms (Azure IaaS, AKS, ADLS, ADF; AWS/GCP a plus).
Strong troubleshooting and engineering mindset with proven production experience.
Nice to Have:
Experience with both Hadoop and Cassandra.
Exposure to Spark, Hive, HBase, or other big data ecosystems.
HPC cluster experience.
Familiarity with AutoSys, ServiceNow, JIRA, Confluence.
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