{"id":1571483,"url":"https://alion.io/job/scor-quant-devops-engineer","title":"Quant DevOps Engineer","company":{"id":1816594,"name":"SCOR","domain":"scor.com","url":"https://alion.io/company/scor-com","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":91,"open_postings":40,"ghost_share":0,"stale_share":0.15,"repost_share":0,"time_to_fill_p50_days":80,"computed_at":"2026-10-06T05:45:30Z"}},"role":"DevOps","role_family":"DevOps","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Zurich, Switzerland"],"countries":["CH"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":83000,"max_usd":205000,"period":"year","method":"role_country_seniority_unknown","sample_n":37},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Configuration Management","optional":false},{"name":"Databricks","optional":false},{"name":"Docker","optional":false},{"name":"Grafana","optional":false},{"name":"Prometheus","optional":false},{"name":"SaltStack","optional":false},{"name":"Snyk","optional":false},{"name":"Terraform","optional":false},{"name":"Wiz","optional":false}],"status":"live","first_seen_at":"2026-05-22T06:42:16Z","employer_posted_date":"2026-05-22","last_verified_at":"2026-10-06T22:43:21Z","board_verified":true,"closed_at":null,"days_open":137,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":136},"description":"The Quant DevOps Engineer owns and operates the application engineering platform, cloud infrastructure, and data execution environment that application and modeling workloads depend on.\nThe role is accountable for the 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.\nThis position requires broad and deep technical expertise, strong operational judgment, and the ability to act as a central technical interface between engineering teams, IT operations, security/SecOps, and data users. It is a senior ownership role with significant impact on delivery speed, platform stability, and infrastructure cost.\n Platform & Infrastructure Ownership\nEnd-to-end ownership and delivery accountability for the application execution platform and production model runs (Databricks, Servers).\nDay-to-day operational responsibility: availability, incident handling, runtime management, and delivery continuity for business-critical runs (incl. peak periods like YE).\nManage Azure cloud infrastructure, including: Virtual machines, storage, identity and access management (RBAC)\nNetworking components such as firewalls, peering, and cross-subscription connectivity\n\nLead standardization with central teams across observability, security controls, platform services, and “golden paths,” while keeping delivery running\nEnsure platform reliability, scalability, and long-term sustainability\nCI/CD & Automation\nDesign, maintain, and continuously improve CI/CD pipelines using Azure DevOps and related tooling\nBuild and evolve automation using scripting and build tools\nOptimize pipeline performance, reliability, and parallel execution to support large-scale workloads\nContainer & Runtime Management\nOwn Docker image creation, lifecycle management, and governance\nOptimize build processes, caching strategies, and container security\nSupport containerized execution environments for compute-heavy workloads and services\nInfrastructure as Code & Configuration Management\nMaintain and evolve Infrastructure as Code using Terraform\nOperate and improve configuration management systems (e.g. SaltStack)\nReduce configuration drift and improve reproducibility across environments\nObservability, Security & Secrets\nOwn and operate observability platforms (e.g. ELK, Prometheus, Grafana)\nEnsure meaningful metrics, logs, dashboards, and alerting are in place\nManage secrets and platform security tooling (e.g. Wiz, Snyk)\nCollaborate closely with Security and SecOps teams on controls, findings, and improvements\nData Platform & Capacity Planning\nConfigure/support Databricks usage for application workloads; manage workspace-level configuration/permissions as delegated; partner with central Databricks lead for global administration and optimization.\nSupport large-scale data and compute workloads\nLead capacity planning for: Highly parallel Databricks clusters (e.g. up to ~10 × 80-node clusters)\nMemory-intensive systems (multi-terabyte RAM)\nData pipelines producing terabytes of data\n\nBalance performance, reliability, and cost across platform decisions\nOperations & Incident Response\nAct as senior escalation point for platform and infrastructure incidents\nParticipate in a limited on-call rotation\nInvestigate incidents and execute or coordinate remediation\nPerform manual interventions when automation is insufficient\nDrive post-incident reviews and platform improvements\nCross-Team & Organizational Coordination\nServe as primary technical contact for: IT Operations\nSecurity and SecOps\nArchitecture and governance bodies\nService management processes\n\nCoordinate platform-related work across teams\nSupport customer-facing technical discussions related to platform capabilities and constraints\n Experience\nBackground in Insurance, Finance, or Scientific / High-Performance Computing environments\nStrong experience in platform or DevOps engineering within production environments\nSolid expertise in cloud infrastructure, preferably Microsoft Azure\nHands-on experience with CI/CD, Infrastructure as Code, and container platforms\nProven experience operating data-intensive and compute-heavy systems\nTechnical Competencies\nStrong troubleshooting and operational mindset\nAbility to manage and balance competing constraints: Cost\nPerformance\nSecurity\nReliability\n\nDeep understanding of platform stability, scalability, and automation\nProfessional Competencies\nSenior-level autonomy and decision-making capability\nOwnership mindset; 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