Sofian DAGHSEN

– Software QA Team Lead for the Healthdata.be platform, leading a multidisciplinary QA and test engineering team responsible for functional, non-functional, and performance validation of a national-scale health data system. – Owned quality strategy, test governance, and release-readiness criteria, ensuring that functional correctness, performance, and reliability risks were addressed before national production rollouts. – Led and mentored test engineers, driving adoption of automation-first practices and embedding quality gates into CI/CD pipelines. – Acted as the primary quality and risk interface between engineering, product, and stakeholders, translating technical risk into actionable go/no-go decisions for national data-collection releases.

– Principal Performance & Quality Architect for Belgium's national health data platform (Healthdata.be), serving 11.6M citizens and ingesting data from 500+ laboratories and hospitals under strict GDPR and availability constraints. – Owned end-to-end performance architecture for a distributed, cloud-native system, defining scalability limits, tail-latency behavior (p95/p99), and architectural quality gates for national-scale data ingestion. – Identified critical scalability ceilings (heap exhaustion, GC thrashing, ingestion breakpoints) and architected stream-processing and backpressure solutions, achieving 3x load capacity and preventing production failures during national data-collection windows. – Embedded automated performance and regression validation into CI/CD, reducing performance regression detection time by ~50% and preventing 15+ high-risk issues from reaching production.

– Senior Automation & Quality Architect for a global licensing platform governing activation of FDA-regulated medical and industrial 3D-printing software. – Owned the global quality architecture for the licensing ecosystem, defining testing-pyramid strategy and embedding automated validation as an immutable gate in CI/CD. – Resolved critical concurrency and caching bottlenecks using Intel VTune and Valgrind, preventing entitlement failures during concurrent license activations and long-running sessions. – Increased automated test depth from <40% to >90%, reduced manual regression effort by ~80%, and prevented revenue-impacting defects in mission-critical customer environments.

– Lead Test Automation & Performance Architect (Test Automation Lead) for a mission-critical, real-time traffic enforcement platform used by Belgian Federal Police. – Owned performance and resilience architecture for a distributed, containerized system, defining scalability limits, failover behavior, and architectural quality gates. – Improved end-to-end throughput by ~30%, validated RTO <30s / RPO = 0, and embedded automated performance & failover validation into CI/CD.

– SDET Lead and Architect (Test Automation & Performance) providing non-functional validation strategy and architectural risk assessments for public-sector and enterprise clients. – Acted as technical authority for performance, scalability, and release readiness, advising engineering leadership and C-level stakeholders on high-availability system modernization. – Defined enterprise performance strategies, KPIs, and automated quality gates aligned with business SLAs, preventing high-risk launch failures in large-scale client migrations. – Recognized as "Best Consultant – Business Impact" (2018-2019) and subsequently headhunted by MACQ SA to architect their national-scale mobility platform internally.

– Automotive Software Test Engineer for BMW Group automotive platforms, working on safety-critical body-control and vehicle-electronics systems (BDC 2015 / 2018). – Automated system level tests following requirements-based testing model. – Performed software and hardware verification and validation under ISO-26262 and V-Model development constraints, ensuring functional correctness and compliance for production releases. – Led requirements analysis and bidirectional traceability using IBM DOORS; designed and executed system, integration, and exploratory test scenarios across AUTOSAR-based environments. – Contributed to early defect discovery beyond formal specifications, improving system robustness and establishing a strong foundation in disciplined, safety-critical engineering.