Site Reliability Engineer (SRE) – Federal Cloud Analytics

Job Description

Analytics Sr Software Engineer (US Federal) | Workday

The Tone:
This is a hybrid role at Workday, located in Reston, VA. Workday builds a leading AI platform for managing people, money, and agents, shaping the future of work. This role is crucial for supporting U.S. federal agencies as they modernize and transform their employee lifecycle and finance operations. The work directly contributes to ensuring these agencies operate with greater clarity, accountability, and trust by delivering secure and reliable analytics within a government cloud environment.

The TL;DR
• Role: Full Time
• Location: Hybrid – Reston, VA
• Pay: $137100–$243600 yearly
• Team: Analytics Delivery Engineering team (SRE)
• Mission: Build a clean, scalable, reliable, and automated services framework to deliver Workday Analytics to GovCloud for U.S. Federal agencies.
• Tech Stack: Kubernetes, Terraform, Argo CD, GoLang, Python, Prometheus, Grafana, Apache Spark, Hadoop, HDFS, Storm, Docker

What You’ll Actually Do
• Automation: Build out robust CI/CD and automation solutions for both the Prism engineering team and the SRE team.
• Observability: Enhance and improve monitoring, alerting, and tracing for internal and production services.
• Platform Development: Design, develop, and implement solutions for the Kubernetes platform, including infrastructure automation and CI/CD pipelines.
• Infrastructure Management: Automate infrastructure provisioning, configuration management, and application deployments using tools like Terraform and Argo CD.
• Reliability Engineering: Participate in production on-call duties and events to ensure the reliability of analytics applications in GovCloud deployments.

The Must-Haves
• Background: United States citizenship (naturalized or native) is required. Bachelor’s degree in a computer-related field or equivalent work experience with a deep understanding of systems architecture, networking, and security within infrastructure environments.
• Experience: 5+ years of hands-on experience with infrastructure (on-premises or cloud-based); 5+ years of experience in GoLang or Python; 2+ years of experience with Kubernetes concepts, architecture, and administration; 3+ years experience working with AWS cloud services in a production setting.
• Skills: Proficiency in infrastructure automation tools like Terraform; experience with building or maintaining CI/CD pipelines and tools like Argo CD; strong analytical and problem-solving skills; excellent communication and collaboration skills.
• Bonus: An active TS/SCI w/CI Poly clearance is preferred (or the ability to obtain and maintain one); preferred DoD 8570/8140 compliant with at least IAT Level II certification (including a current Computing Environment credential and one approved specialty certification); expertise in Object-Relational Mapping (ORM), big data technologies (Apache Spark, Hadoop, HDFS, Storm), data pipeline development, and data lake architecture; experience with monitoring and observability tools (Prometheus, Grafana); experience with security auditing and compliance frameworks; experience with Docker.