Groupon is a marketplace where customers discover new experiences and services everyday and local businesses thrive. To date we have worked with over a million merchant partners worldwide, connecting over 16 million customers with deals across various categories. In a world often dominated by e-commerce giants, we stand out as one of the few platforms uniquely committed to helping local businesses succeed on a performance basis.
Groupon is on a radical journey to transform our business with relentless pursuit of results. Even with thousands of employees spread across multiple continents, we still maintain a culture that inspires innovation, rewards risk-taking and celebrates success. The impact here can be immediate due to our scale and the speed of our transformation. We're a "best of both worlds" kind of company. We're big enough to have the resources and scale, but small enough that a single person has a surprising amount of autonomy and can make a meaningful impact.
We're committed to building smarter, faster, and more innovative ways of working—and AI plays a key role in how we get there. We encourage candidates to leverage AI tools during the hiring process where it adds value, and we're always keen to hear how technology improves the way you work. If you're passionate about AI or curious to explore how it can elevate your role—you'll be right at home here.
About the Role
At Groupon, we are in the midst of a rapid and high-impact platform transformation—modernizing core infrastructure to power the next chapter of our business. As the Engineering Manager, Observability & CI/CD, you'll own the full lifecycle of platform evolution, leading both strategic migrations and daily operations for our Observability and CI/CD systems that underpin the productivity of 300+ fellow engineers.
This is not a maintenance role—it's a player-coach opportunity for a true builder. Your mission: Lead our teams through must-win migrations (from Jenkins to GitHub Actions and ELK to GCP Native Logging), maximize the impact of AI-augmented workflows, and ensure Groupon continues to deliver reliable, rapid innovation at global scale.
Key Responsibilities
Lead & Mentor: Manage and develop a distributed CI/CD & Observability engineering team, fostering a high-performance, growth-oriented culture.
Drive Migrations: Execute critical platform transitions, especially Jenkins-to-GitHub Actions for CI/CD and ELK-to-GCP Logging for Observability—owning milestone tracking and ensuring on-time, no-straggler migration.
AI "Migration Factory": Integrate AI tools (Claude Code, sub-agents) into your team's daily workflow—predict and measure time savings, optimize pipeline/tooling, and show tangible process gains.
Platform Reliability & Efficiency: Oversee the hardening and scaling of our Observability stack (Grafana, Prometheus/Thanos), optimize reliability and cost, and deliver clear SLAs.
Stakeholder Alignment: Collaborate tightly with C-level, product leaders, and business partners to define and deliver on shared priorities.
Role Requirements
Must-haves:
3–5+ years' experience leading technical teams in infrastructure, DevOps, platform, or SRE domains. We can be flexible on this requirement and we are ready to support you if you are open to leadership. To us, deep technical & hands-on experience is key.
Proven track record managing end-to-end technical migrations at scale (ideally in CI/CD or Observability/Logging/Monitoring).
Deep fluency with core technologies: GCP (Google Cloud), Kubernetes, Jenkins, GitHub Actions, Grafana, Prometheus/Thanos, ELK Stack, Infrastructure as Code (Terraform, Ansible).
Demonstrated ability to develop, coach, and inspire a globally distributed team.
Strong analytical and problem-solving skills; ability to engage technically and strategically with both teams and C-suite.
Bachelor's or Master's in Computer Science, Engineering or a relevant field.
Excellent communication skills in English.
Nice-to-haves:
Experience with large-scale cloud consolidation projects and migrations (AWS to GCP a plus).
Familiarity with modern, high-throughput database and event-processing stacks.
Past experience implementing or leading AIOps/AI-augmented engineering initiatives.
Prior work in a high change, scale-up, or turnaround environment.