Software Engineer, Data & Observability Platforms — MTS/SMTS

Design, build, and operate telemetry, observability, logging, and alerting systems that provide real-time visibility into system health, reliability, and performance.

Advance our observability platform beyond dashboards and reactive monitoring toward proactive, AI- and agent-assisted issue detection, investigation, and root-cause analysis.

Build and evolve data pipelines and platform services that integrate data from Workday, Salesforce, and other enterprise systems.

Enable operational, reporting, analytics, and emerging AI and agentic use cases through reliable, secure, and well-governed data.

Build and improve CI/CD pipelines with integrated quality gates, including automated testing, security scanning, and vulnerability checks.

Develop scalable and maintainable infrastructure and services using open-source technologies, primarily on AWS, with some workloads on GCP.

Partner with Employee Success, Finance, security, data, and other engineering teams to identify platform gaps and improve developer experience, data reliability, and operational intelligence.

Participate in architecture discussions, design reviews, code reviews, and technical planning.

Apply and promote engineering best practices related to code quality, testing, security, reliability, and operational excellence.

Contribute to reusable technical patterns, standards, and documentation across the platform.

Professional software development experience building and operating production systems.

Proficiency in one or more relevant programming languages, such as Java, Python, or Go.

Experience with—or a strong interest in—observability, telemetry, logging, alerting, data pipelines, or data platforms.

Familiarity with open-source technologies and modern software engineering practices.

Experience with CI/CD pipelines, automated testing, and foundational security or vulnerability-management practices.

Working knowledge of cloud infrastructure, particularly AWS; GCP experience is a plus.

Understanding of distributed systems, scalability, reliability, and system-design principles.

Strong collaboration and communication skills, with the ability to work effectively across engineering and business teams.

Bachelor’s degree in Computer Science, Engineering, a related field, or equivalent practical experience.

Typically 3–5 years of professional software development experience, or equivalent demonstrated capability.

Experience implementing well-defined services, platform components, or data pipelines.

Ability to deliver reliable solutions with guidance from senior engineers.

Willingness to incorporate feedback and develop deeper expertise in platform, data, and observability engineering.

Ability to take ownership of components and contribute effectively to technical discussions and code reviews.

Typically 8 or more years of professional software development experience, or equivalent demonstrated capability.

Demonstrated experience designing and operating scalable platforms, shared services, infrastructure, or developer capabilities used by multiple teams.

Ability to independently lead complex technical initiatives from architecture through production operation.

Strong architectural judgment and the ability to make pragmatic tradeoffs across scalability, reliability, security, and delivery.

Experience influencing cross-functional stakeholders, driving technical alignment, and establishing reusable engineering standards.

Ability to mentor other engineers and raise the technical effectiveness of the broader team.

Experience applying AI or agentic approaches to observability, incident investigation, monitoring, or operational tooling.

Experience integrating Workday, Salesforce, or other enterprise and third-party systems.

Experience with MuleSoft or a similar enterprise integration platform.

Experience with Kubernetes or another container-orchestration platform.

Familiarity with infrastructure-as-code tools such as Terraform or CloudFormation.