Serve as a primary escalation point for production support involving Airflow and UC4 – assisting end-user inquiries, incident root cause analysis, and implementing go-forward solutions
Own and continuously improve SLOs, SLIs, and error budgets for orchestration platforms
Monitor platform health, capacity, and performance; proactively identify and remediate issues before they impact users
Partner with data engineering and application teams to troubleshoot DAG failures, job dependencies, and scheduling issues
Manage patching, upgrades, and configuration management for Airflow and UC4 environments
Collaborate with security to harden platform configurations and manage software vulnerabilities
Contribute to on-call rotations and maintain runbooks and escalation procedures
Design and build tooling and automation to reduce toil and improve developer experience for teams that depend on Airflow and UC4
Lead or contribute to platform modernization initiatives– e.g., migrating workloads, improving deployment pipelines, containerizing components, or adopting managed service offerings
Develop and maintain infrastructure-as-code (Terraform, Helm, Ansible, etc.) for platform components
Build observability solutions (e.g., dashboards, alerting, log aggregation) that give teams better visibility into their workflows
Build and enforce standards around platform use that help engineering teams adopt best practices at scale
Participate in design reviews and contribute to the overall platform roadmap

Bachelor’s degree in a technical field or equivalent practical experience
5+ years of experience in SRE, DevOps, or platform engineering roles
Deep hands-on experience with Apache Airflow – ideally including distributed executor configurations (Celery or Kubernetes), DAG authoring best practices, and multi-environment deployments
Experience operating enterprise job scheduling platforms (e.g., Automic/UC4, Control-M, etc.)
Strong Linux and Windows systems knowledge and comfort working in cloud environments (AWS preferred)
Proficiency in Python for automation and tooling; familiarity with shell scripting
Experience with container orchestration (Kubernetes, Docker) and CI/CD pipelines
Solid understanding of observability principles – metrics, logging, tracing – and tools like ELK, Grafana, and Prometheus
Demonstrated ability to drive incidents to resolution and communicate clearly under pressure
A bias toward automation and a low tolerance for repetitive manual work

Senior Site Reliability Engineer – Workflow Automation

Key skills