Company Description
We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale — across all devices and digital mediums, and our people exist everywhere in the world (15000+ experts across 26 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in!
Job Description
This hybrid role bridges Data Operations, DevOps, and Infrastructure Support, ensuring data-driven systems remain reliable, performant, and continuously optimized.
Responsibilities:
- Manage end-to-end data and infrastructure operations, from writing SQL queries to CI/CD pipeline creation and optimization and VM and cloud-based deployments.
- Drive incident and request management through ServiceNow, ensuring SLA compliance, ownership, and proactive issue resolution.
- Implement and refine monitoring and observability frameworks using Datadog; Grafana; Prometheus to maintain uptime, identify bottlenecks, and enhance system reliability.
- Collaborate across global teams including Data Engineering, Product, and IT Infrastructure to resolve production issues, improve deployment practices, and optimize system performance.
- Conduct root cause analyses and contribute to blameless post-incident reviews and preventive action plans.
- Collaborate with security and compliance teams to uphold operational standards and data protection practices.
- Contribute to automation and continuous improvement initiatives through scripting (Python, Shell) and infrastructure-as-code (Terraform, Ansible) principles.
- Support the data lifecycle, ensuring accuracy, integrity, and accessibility of data pipelines and dashboards across analytics platforms.
- Collaborate with Data Engineering teams to ensure data pipelines, ETL processes, and analytics platforms are performant, reliable, and production-ready.
- Collaborate on capacity planning, scaling, and performance optimization to ensure reliability during growth and high-load scenarios.
- Use operational metrics (MTTR, uptime, failure rate, latency) to drive service reliability improvements.
- Participate in Agile ceremonies within a Scrum/Kanban model, aligning with delivery squads to ensure cross-functional visibility and operational excellence.
- Operate within a 24-5 rotational model, supporting mission-critical environments and ensuring business continuity across time zones.
What You Will Bring Experience:
6 to 8+ years in DataOps, DevOps, infrastructure operations, site reliability engineering or analytics platform support.
Technical Expertise:
- Intermediate SQL for data extraction, transformation, and diagnostics.
- Strong understanding of CI/CD pipelines (Jenkins, Azure DevOps, Git-based version control).
- Proficiency in monitoring and observability tools (Datadog, Grafana, Prometheus).
- Hands-on with Python or Shell scripting for automation and diagnostics.
- Familiarity with containerization (Docker, Kubernetes) and cloud platforms (AWS, Azure, GCP). Knowledge of AWS services is a must.
- Solid grasp of infrastructure-as-code concepts (Terraform, Ansible).
Operational Excellence:
Proven record in incident management, maintaining SLA/SLI/SLO s for critical systems and escalation handling in enterprise environments.
Analytical Mindset:
Ability to interpret system and data metrics, identify trends, and recommend performance improvements.
Collaboration:
Strong communication skills with cross-functional, global teams across technical and non-technical domains.
Agility:
Comfort working in dynamic, fast-paced environments, maintaining composure and prioritization under pressure.
Qualifications
Must have Skills:
SQL (Strong), DevOps - AWS (Strong), Python (Strong), CI/CD pipelines.
Good To Have Skills:
Datadog; Grafana; Prometheus.
Service Region:
UCC