BigData DevOps Engineer

Experian

3d•Remote

About The Position

As an important aide to both the IT Infrastructure and Development teams, you will help support existing systems 24x7 and be responsible for administering current Big Data environments. You will manage BigData Group environments and will work with teammates to maintain working solutions for our big data tech stack. To support product development following the product roadmap for product maintenance and enhancement such that the quality of software deliverables maintains excellent customer relationships and increases the customer base. You will report to the Engineering Manager, Data Platforms.

Requirements

Typically requires a bachelor's degree (in Computer Science or related field) or equivalent.
3+ years of Hadoop infrastructure administration – AWS EMR or Cloudera environments
2+ years of Linux (Redhat) system administration
Cloud Platforms IaaS/PaaS – Cloud solutions: AWS, Azure, VMWare.
Automation skills – Ansible and Terraform.
Kerberos administration skills
Experience coding languages SQL, Python
Good experience in CI/CD tools such as Jenkins, Puppet and Shell scripting
Must have knowledge on DevOps tools.
Working Knowledge of YARN, HBase, Hive, Spark, and Kafka.
Experience working with geographically distributed teams
Bachelors or master's degree in Computer Science or equivalent experience

Nice To Haves

Gen AI / Agentic AI knowledge is plus
Knowledge of our strategy and use of back-office applications.
To multi-lingual and multicultural environment, additional language skills are a bonus.
Receptive to change.
With our users at all levels.

Responsibilities

Implement, support, and administer Hadoop and AWS EMR environments.
Maintain Terraform and IaC for provisioning and managing AWS resources.
Provide CI/CD solutions.
Automate deployment and operations of Big Data technologies using DevOps tools.
Onboard Hadoop users and manage Kerberos, HDFS, Hive, HBase, and Yarn access.
Implement security best practices across HBase, HDFS, Kafka, Hive, and related components.
Tune Hadoop clusters, MapReduce, Spark workloads, and optimize EMR for performance and cost.
Monitor group health, logs, storage, and perform proactive capacity management.
Collaborate with infrastructure, network, DB, application, and BI teams to ensure platform reliability.
Support upgrades and patching for EMR, HBase, Spark, and other data platforms.
Troubleshoot system issues and analyze CPU, memory, OS, storage, and network performance.
Deploy and manage Hadoop clusters, configure HA, manage nodes, schedule jobs, and perform backups.
Support integrations across cloud/on‑prem networks and data platforms.
Configure and maintain tools like Sentry, Spark, Kafka, Oozie, Solr, MongoDB, DocumentDB, and ELK.
Integrate AD/LDAP with Cloudera, manage Sentry policies.