Site Reliability Engineer II
Listed on 2026-05-10
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IT/Tech
Cloud Computing, Systems Engineer, SRE/Site Reliability
About this position
We are looking for a talented and driven Site Reliability Engineering (SRE) to support our engineering team, which manages the infrastructure and services that power our Waystar products. This role is ideal for an experienced engineer who thrives in data-intensive environments and is passionate about building reliable, scalable systems that ensure data integrity, availability, and performance.
As an SRE Specialist, you’ll work closely with engineering, product, and data teams to ensure our data licensing platforms are resilient, observable, and continuously improving.
What you’ll do- System Reliability & Performance
- Design and implement reliability solutions for data ingestion, processing, and delivery pipelines.
- Define and maintain SLIs/SLOs for data licensing services and manage error budgets.
- Build automation for deployment, monitoring, and incident response.
- Observability & Monitoring
- Enhance system observability through metrics, logging, and tracing.
- Develop and maintain dashboards and alerts to proactively detect and resolve issues.
- Incident Response & Postmortems
- Participate in on‑call rotations and lead incident response efforts.
- Conduct root cause analysis and drive post‑incident improvements.
- Maintain runbooks and operational documentation.
- Collaboration & Continuous Improvement
- Partner with software and data engineers to embed reliability into system design.
- Contribute to blameless postmortems and reliability reviews.
- Share knowledge and mentor junior team members.
- 2+ years of experience in SRE, Dev Ops, or infrastructure engineering.
- Strong understanding of cloud platforms (AWS, GCP, or Azure), container orchestration (Kubernetes), and infrastructure‑as‑code (Terraform, Cloud Formation).
- Experience with observability tools (Prometheus, Grafana, Splunk) and CI/CD pipelines.
- Familiarity with data platforms, ETL pipelines, and distributed systems.
- Excellent problem‑solving and communication skills.
- Experience with Python, Power Shell, and other similar languages.
- Active use of artificial intelligence (AI) tools and techniques to enhance performance, drive innovation, and improve decision‑making across business functions.
- Ability to leverage AI tools and platforms to streamline workflows, improve decision‑making, and drive innovation.
- Curiosity and adaptability in exploring emerging AI technologies, with a mindset for continuous learning and experimentation.
- Experience with data licensing, data governance, or data compliance frameworks.
- Exposure to data pipeline tools (Apache Airflow, Kafka, Spark).
- Familiarity with regulatory requirements related to data usage and distribution.
- Competitive total rewards (base salary + bonus, if applicable).
- Customizable benefits package (3 medical plans with Health Savings Account company match).
- Generous paid time off for our non‑exempt team members, starting with 3 weeks + 13 paid holidays, including 2 personal floating holidays. Flexible time off for our exempt team members + 13 paid holidays.
- Paid parental leave (including maternity + paternity leave).
- Education assistance opportunities and free Linked In Learning access.
- Free mental health and family planning programs, including adoption assistance and fertility support.
- 401(K) program with company match.
- Pet insurance.
- Employee resource groups.
Waystar is proud to be an equal opportunity workplace. We celebrate, value, and support diversity and inclusion. Qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, marital status, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.
This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.
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