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Staff DevOps Engineer
2 months ago
We are seeking a highly skilled Staff DevOps Engineer - Hadoop Administrator to join our Big Data Federal Team at ServiceNow. As a key member of our team, you will play a critical role in delivering 24x7 support for our Government Cloud infrastructure.
Key Responsibilities- Deploy, production monitor, maintain, and support Big Data infrastructure and applications on ServiceNow Cloud and Azure environments.
- Architect and drive the end-to-end Big Data deployment automation from vision to delivering the automation of Big Data foundational modules (Cloudera CDP), prerequisite components, and Applications leveraging Ansible, Puppet, Terraform, Jenkins, Docker, Kubernetes.
- Automate Continuous Integration / Continuous Deployment (CI/CD) data pipelines for applications leveraging tools such as Jenkins, Ansible, and Docker.
- Performance tune and troubleshoot various Hadoop components and other data analytics tools in the environment: HDFS, YARN, Hive, HBase, Spark, Kafka, RabbitMQ, Impala, Kudu, Redis, Hue, Kerberos, Tableau, Grafana, MariaDB, and Prometheus.
- Provide production support to resolve critical Big Data pipelines and application issues and mitigate or minimize any impact on Big Data applications.
- Collaborate closely with Site Reliability Engineers (SRE), Customer Support (CS), Developers, QA, and System engineering teams in replicating complex issues leveraging broad experience with UI, SQL, Full-stack, and Big Data technologies.
- Enforce data governance policies in Commercial and Regulated Big Data environments.
- A 4-day workweek (Wednesday to Saturday or Sunday to Wednesday)
- No on-call rotation
- Shift bonuses for 2nd and 3rd shifts
The Big Data team plays a critical and strategic role in ensuring that ServiceNow can exceed the availability and performance SLAs of the ServiceNow Platform powered Customer instances - deployed across the ServiceNow cloud and Azure cloud. Our mission is to deliver state-of-the-art Monitoring, Analytics, and Actionable Business Insights by employing new tools, Big Data systems, Enterprise Data Lake, AI, and Machine Learning methodologies that improve efficiencies across a variety of functions in the company: Cloud Operations, Customer Support, Product Usage Analytics, Product Upsell Opportunities, enabling to have a significant impact both on the top-line and bottom-line growth.