Senior Hadoop Admin - Big Data - Federal - 2nd Shift

Company Description

It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today — ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone.

Job Description

Please Note:  This position will include supporting our US Federal Government Cloud Infrastructure.

This position requires passing a ServiceNow background screening, USFedPASS (US Federal Personnel Authorization Screening Standards). This includes a credit check, criminal/misdemeanor check and taking a drug test. Any employment is contingent upon passing the screening.  Due to Federal requirements, only US citizens, US naturalized citizens or US Permanent Residents, holding a green card, will be considered.

As a Staff DevOps Engineer on our Big Data Federal Team, you will help deliver 24x7 support for our Government Cloud infrastructure.

The Federal Big Data Team has 3 shifts that provide 24x7 production support for our Big Data Government cloud infrastructure. 
This is a 2nd Shift Position - Sunday to Wednesday with work hours from 3 pm Pacific Time to 2 am Pacific Time

Below are some highlights.

• 4 Day work week (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. The Big Data team is responsible for:

• Collecting, storing, and providing real-time access to large amount of data
• Provide real-time analytic tools and reporting capabilities for various functions including:
  • Monitoring, alerting, and troubleshooting
  • Machine Learning, Anomaly detection and Prediction of P1s
  • Capacity planning
  • Data analytics and deriving Actionable Business Insights

What you get to do in this role

• Responsible for deploying, production monitoring, maintaining and supporting Big Data infrastructure, Applications on ServiceNow Cloud and Azure environments.
• Deploy, scale, and manage containerized applications using Kubernetes, docker, and other related tools.
• Automate Continuous Integration / Continuous Deployment (CI/CD) data pipelines for applications leveraging tools such as Jenkins, Ansible, and Docker.
• Proactively identify and resolve issues within Kubernetes clusters, containerized applications, and CI/CD pipelines. Provide expert-level support for incidents and perform root cause analysis.
• Understanding of networking concepts related to containerized environments
• Provide production support to resolve critical Big Data pipelines and application issues and mitigating or minimizing 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.
• Responsible for enforcing data governance policies in Commercial and Regulated Big Data environments.

Qualifications

To be successful in this role you have:

• Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry
• Deep understanding of Hadoop / Big Data Ecosystem.
• 6+ Experience working with systems such as HDFS, Yarn, Hive, HBase, Kafka, RabbitMQ, Impala, Kudu, Redis, MariaDB, and PostgreSQL
• Hands-on experi