Associate Staff Engineer - DataOps

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 Must have Skills: SQL (Strong), DevOps - AWS (Strong), Python (Strong), CI/CD pipelines Good To Have Skills: Datadog; Grafana; Prometheus 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!