Quant DevOps Engineer

The Quant DevOps Engineer is responsible for the reliability, scalability, security, and cost efficiency of large-scale, data-intensive cloud workloads.

• Own and operate the application engineering platform, cloud infrastructure, and data execution environment for application and modeling workloads.
• Ensure end-to-end reliability, scalability, security, performance, and cost efficiency of the platform, supporting large-scale, data-intensive and compute-heavy workloads such as parallel Databricks clusters and high-memory systems.
• Act as a central technical interface between engineering teams, IT operations, security/SecOps, and data users.
• End-to-end ownership and delivery accountability for the application execution platform and production model runs (Databricks, Servers).
• Day-to-day operational responsibility: availability, incident handling, runtime management, and delivery continuity for business-critical runs, including peak periods.
• Manage Azure cloud infrastructure, including virtual machines, storage, identity and access management (RBAC), and networking components such as firewalls, peering, and cross-subscription connectivity.
• Lead standardization with central teams across observability, security controls, platform services, and "golden paths," while maintaining delivery continuity.
• Design, maintain, and continuously improve CI/CD pipelines using Azure DevOps and related tooling.
• Build and evolve automation using scripting and build tools.
• Optimize pipeline performance, reliability, and parallel execution for large-scale workloads.
• Own Docker image creation, lifecycle management, and governance.
• Optimize build processes, caching strategies, and container security.
• Support containerized execution environments for compute-heavy workloads and services.
• Maintain and evolve Infrastructure as Code using Terraform.
• Operate and improve configuration management systems (e.g. SaltStack).
• Reduce configuration drift and improve reproducibility across environments.
• Own and operate observability platforms (e.g. ELK, Prometheus, Grafana).
• Ensure meaningful metrics, logs, dashboards, and alerting are in place.
• Manage secrets and platform security tooling (e.g. Wiz, Snyk).
• Collaborate closely with Security and SecOps teams on controls, findings, and improvements.
• Configure/support Databricks usage for application workloads; manage workspace-level configuration/permissions as delegated; partner with central Databricks lead for global administration and optimization.
• Support large-scale data and compute workloads.
• Lead capacity planning for highly parallel Databricks clusters (e.g. up to ~10 × 80-node clusters), memory-intensive systems (multi-terabyte RAM), and data pipelines producing terabytes of data.
• Balance performance, reliability, and cost across platform decisions.
• Act as senior escalation point for platform and infrastructure incidents.
• Participate in a limited on-call rotation.
• Investigate incidents and execute or coordinate remediation.
• Perform manual interventions when automation is insufficient.
• Drive post-incident reviews and platform improvements.
• Serve as primary technical contact for IT Operations, Security and SecOps, architecture and governance bodies, and service management processes.
• Coordinate platform-related work across teams.
• Support customer-facing technical discussions related to platform capabilities and constraints.