مهندس حلول أول

This is a technical leadership role rather than a hands-on development role: the architect owns the technical integrity of the solution and leads, reviews and challenges multidisciplinary engineering teams, without personally developing applications, ETL pipelines or platform components.

Responsibilities

1. Own and maintain the end-to-end solution architecture across application, data, integration, cloud, security and analytics domains.
2. Translate business, functional and non-functional requirements into coherent and implementable technical solutions.
3. Define architecture principles, patterns, interfaces and major technical decisions, and record them.
4. Lead and provide technical direction to multidisciplinary engineering and delivery teams.
5. Coordinate specialist architects and technical leads where available, and work directly with engineers where required.
6. Review solution designs and implementation approaches and ensure alignment with the approved architecture.
7. Lead the implementation of an overarching Quality Management approach covering the end-to-end solution lifecycle — architecture, data, applications, integrations, infrastructure, security, testing, deployment and operations.
8. Establish quality standards, controls, acceptance criteria, quality gates, review mechanisms and automated testing practices to ensure solution reliability, consistency and maintainability.
9. Govern and continuously assess solution quality throughout delivery — monitoring quality performance, identifying defects and systemic quality risks, driving root-cause analysis and corrective action, and promoting continuous improvement.
10. Lead resolution of complex technical issues and cross-domain dependencies.
11. Ensure security, privacy, data governance, quality, performance, scalability, availability and maintainability requirements are addressed.
12. Ensure appropriate DevOps, automation, testing, monitoring and engineering-quality practices are incorporated into delivery.
13. Assess technical risks, technical debt and solution/release readiness.
14. Work closely with Project Managers on technical estimation, planning, sequencing, dependencies, risks, progress and delivery readiness.
15. Provide clear technical reporting, and communicate complex architecture matters to management and non-technical stakeholders.

Qualifications

Required: Bachelor’s degree in computer science, Software Engineering, Information Systems, Computer Engineering or a related technical discipline.
Required: 12 + years in technology roles, of which at least 5 in Solution Architecture, Technical Architecture or comparable technical leadership, with the most recent role held in an architecture or technical leadership capacity.
Required: Proven delivery of complex enterprise solutions combining data platforms and applications, and experience leading multidisciplinary technical teams across the full solution delivery lifecycle.
Required: Personal authorship of core architecture artifacts — solution and interface designs, integration designs, non-functional requirements, security designs and architecture decision records.
• End-to-End Solution Architecture: integrated solutions spanning source systems, ingestion, processing, governance, semantic layers, analytics, APIs and web applications.
• Data Platform Architecture: ETL/ELT, data integration, transformation, curation, modelling, data quality, metadata, cataloguing, lineage, governance, MDM/RDM and semantic layers.
• Application & Integration Architecture: modern web architectures, APIs, API gateways, microservices, containers, Kubernetes and distributed application patterns.
• Cloud & Platform Architecture: cloud and hybrid architectures, scalability, resilience, networking, compute, storage, observability and platform integration.
• Security & Privacy Architecture: IAM, RBAC/ABAC, API security, encryption, masking, tokenization, data privacy, row/column-level security and secure development practices.
• Analytics & AI/ML: descriptive, diagnostic, predictive and prescriptive analytics, semantic modelling and machine-learning concepts.
• DevOps & Quality Engineering: Git, CI/CD, release management, deployment automation, and automated quality practices including unit, integration, regression, performance, SAST and DAST testing.
• Agile Technical Delivery: Scrum, Kanban, backlog refinement, technical decomposition, dependency management, technical debt and release planning.