At CVS Health, we’re building a world of health around every consumer and surrounding ourselves with dedicated colleagues who are passionate about transforming health care.

As the nation’s leading health solutions company, we reach millions of Americans through our local presence, digital channels and more than 300,000 purpose-driven colleagues – caring for people where, when and how they choose in a way that is uniquely more connected, more convenient and more compassionate. And we do it all with heart, each and every day.

The Staff Engineer – SRE, Retail & Pharmacy will implement and maintain comprehensive observability solutions, providing real-time insights into the performance and overall health of systems to proactively identify and address potential issues. This role is responsible for investigating and resolving incidents quickly during critical situations and performing root cause analysis to prevent future recurrence. You will collaborate with cross-functional teams to build robust monitoring, alerting, and telemetry solutions, enabling proactive issue detection and resolution across distributed systems. As a senior member of the SRE team, you will drive best practices, mentor others, and shape the strategic evolution of our observability ecosystem in a complex, edge-centric architecture.

What You Will Do:

Observability Strategy & ImplementationDesign and implement comprehensive observability solutions tailored for edge computing environments, including monitoring, logging, tracing, and metrics collection, to provide deep visibility into system performance and health across distributed remote facilitiesDefine and maintain Service Level Indicators (SLIs), Service Level Objectives (SLOs), and business KPIs to measure and enhance system reliability in edge and centralized infrastructureBuild and optimize dashboards, visualizations, and alerting systems to enable real-time insights and rapid incident response for edge nodes and remote facilitiesImplement distributed tracing and log aggregation systems to troubleshoot complex issues in edge computing environments

System Reliability & Performance Collaborate with engineering teams to ensure applications and infrastructure at edge locations are designed with observability in mind, incorporating best practices for instrumentation and monitoring in resource-constrained environmentsDrive proactive identification of issues in edge facilities through advanced observability tools, reducing Mean Time to Detect (MTTD) and Mean Time to Resolve (MTTR) across distributed systemsLead incident postmortems, analyzing root causes specific to edge environments and implementing observability-driven improvements to prevent recurrence

Tooling & Automation Develop and maintain tools, scripts, and automation to enhance observability pipelines, optimizing for the unique challenges of edge computing, such as bandwidth limitations and intermittent connectivityEvaluate and integrate industry-standard observability tools (e.g., Prometheus, Grafana, ELK Stack, OpenTelemetry) and recommend solutions tailored for edge computing use casesOptimize observability data storage, retention, and querying to balance performance, cost, and scalability across a large number of remote facilities

Leadership & Collaboration:Mentor and guide junior SREs and engineers on observability best practices for edge computing, fostering a culture of reliability and proactive monitoringPartner with solution, engineering, and business teams to align observability efforts with business objectives, ensuring seamless operation of edge and centralized systemsLead cross-functional initiatives to improve observability, reliability, and operational efficiency across distributed edge infrastructure

Continuous Improvement:Stay current with emerging observability trends, tools, and methodologies, particularly those suited for edge computing and distributed systems, and advocate for their adoptionContribute to the development of observability standards, runbooks, and documentation tailored for edge environments to ensure consistency and scalabilityDrive cost optimization for observability infrastructure while maintaining high-quality monitoring and alerting capabilities across remote facilities

Minimum Qualifications:

8+ years of experience in SRE, DevOps, or related technology roles5+ years of experience in delivering software in a large-scale environment with reliability and resilience concepts (multi-region, multi-cloud, containerization, etc.)5+ years of experience with observability and monitoring tools such as Splunk, Dynatrace, Datadog, Prometheus, Grafana, etc.3+ years of experience with programming/scripting languages (e.g., Python, java) for automation and tooling in distributed environments3+ years of experience on Cloud Technologies (AWS, Microsoft Azure, Google Cloud3+ years of experience with source control and continuous integration tools like Git/Stash, BitBucket, or Jenkins2+ years of engineering team leadership or management experienceExperience using customer feedback tools such as Quantum Metrics, Medalia, and Adobe AnalyticsDeep understanding of microservices architecture and cloud-native technologiesExperience in configuring, supporting, and managing Rancher, Kubernetes, and/or DockerExperience in Incident Management, Change Management, Infrastructure Support, and Problem Management concepts and processesExcellent interpersonal and communication skills, including the ability to engage technical and non-technical stakeholders

Preferred Qualifications:

Expertise working in edge computing environments with a large number of remote facilities, managing observability for distributed, high-latency, or resource-constrained systemsFamiliarity with chaos engineering principles to validate observability systems in edge environmentsExperience with retail SRE organizations, including experience with store systems; Point of Sale (POS), hand-helds, etc.Expertise in cloud development and deployment technologies, including containerization and multi-cloud configurationsDemonstrated understanding of various API management and related platforms like Apigee, Vordel, Data power

Education:

Bachelor’s degree in Computer Science, Engineering, or related field requiredMaster’s degree in Computer Science, Engineering, or related field preferred

Pay Range

The typical pay range for this role is:

$118,450.00 - $284,280.00

This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls.  The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors.  This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above.  This position also includes an award target in the company’s equity award program. 
 

Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong.

Great benefits for great people

We take pride in our comprehensive and competitive mix of pay and benefits – investing in the physical, emotional and financial wellness of our colleagues and their families to help them be the healthiest they can be. In addition to our competitive wages, our great benefits include:

Affordable medical plan options, a 401(k) plan (including matching company contributions), and an employee stock purchase plan.

No-cost programs for all colleagues including wellness screenings, tobacco cessation and weight management programs, confidential counseling and financial coaching.

Benefit solutions that address the different needs and preferences of our colleagues including paid time off, flexible work schedules, family leave, dependent care resources, colleague assistance programs, tuition assistance, retiree medical access and many other benefits depending on eligibility.

For more information, visit https://jobs.cvshealth.com/us/en/benefits

We anticipate the application window for this opening will close on: 01/30/2026

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.