Join ServiceNow as a Senior Big Data DevOps Engineer

Company Description

At ServiceNow, we create technology that makes the world work for everyone, and our people make it all possible. Our rapid pace reflects the urgency of the world’s demands, driving innovation and excellence for our customers and communities. By becoming part of ServiceNow, you join an ambitious team of change-makers driven by restless curiosity and ingenuity. We believe your best work emerges when you live your best life, so we invest in making that possible. Together, we dream big and support each other to achieve individual and collective aspirations. The future is ours, and it starts with you.

With over 7,700 customers, including approximately 85% of the Fortune 500®, we're honored to be recognized as one of FORTUNE's 100 Best Companies to Work For® and World's Most Admired Companies™. Learn more on our and discover employee experiences at ServiceNow. Unsure if you meet all the qualifications? We encourage you to apply! We are dedicated to creating an inclusive environment where all voices are valued and respected. We welcome all candidates, including those from non-traditional backgrounds. Skills and experience are transferable, and the desire to dream big makes for great candidates.

Job Description

The Big Data team at ServiceNow plays a crucial strategic role, ensuring our platform exceeds availability and performance SLAs for our customers. We leverage cutting-edge tools, Big Data systems, Enterprise Data Lakes, AI, and Machine Learning to deliver state-of-the-art monitoring, analytics, and actionable business insights. This boosts efficiencies across various company functions, including Cloud Operations, Customer Support, and Product Usage Analytics. Join us in driving impactful top-line and bottom-line growth.

Key Responsibilities

• Deploy, monitor, maintain, and support Big Data infrastructure and applications on ServiceNow Cloud and Azure environments.
• Architect and implement end-to-end Big Data deployment automation, utilizing technologies such as Ansible, Puppet, Terraform, Jenkins, Docker, and Kubernetes.
• Automate CI/CD data pipelines with tools like Jenkins, Ansible, and Docker.
• Perform Linux, Bash, and Python scripting.
• Optimize and troubleshoot various Hadoop components and analytics tools: HDFS, YARN, Hive, HBase, Spark, Kafka, RabbitMQ, Impala, Kudu, Redis, Hue, Kerberos, Tableau, Grafana, MariaDB, and Prometheus.
• Provide production support to resolve critical issues in Big Data pipelines and applications.
• Enforce data governance policies in commercial and regulated Big Data environments.
• Collaborate with SREs, Customer Support, Developers, QA, and System Engineering teams to tackle complex issues.

Qualifications

To succeed in this role, you should have:

• 6+ years of experience as a Big Data DevOps/Deployment Engineer.
• Expert-level experience in deployment automation with Puppet, Ansible, Terraform, Jenkins, Docker, Kubernetes, or similar technologies.
• Deep understanding of the Hadoop/Big Data ecosystem.
• Proficiency in querying and analyzing massive datasets using Hive, Spark Streaming, and other tools.
• Experience securing Hadoop stacks using SSL, Ranger, LDAP, and Kerberos KDC.
• Familiarity with CI/CD pipelines on Cloudera, native cloud, and Azure/AWS environments.
• Knowledge of programming languages including Perl, Python, Bash, Groovy, and Java.
• In-depth understanding of Linux internals (RHEL 7.x/8.x) and shell scripting.
• Ability to learn quickly in a dynamic, fast-paced environment.

Additional Information

ServiceNow is an Equal Employment Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. We lead with flexibility and trust in our distributed world of work. : flexible, remote, and required-in-office.

If you need a reasonable accommodation during the