Solution Architect

Position Overview

We are looking for a seasoned Solution Architect with over 10 years of expertise in enterprise solution architecture, data platform engineering, system integration, and advanced data ecosystems spanning on-premises, cloud, and hybrid platforms. This full-time role is based onsite in Riyadh, Saudi Arabia.

The architect will design, oversee, and enhance large-scale technology solutions that align with business goals, adhere to architectural standards, and follow industry best practices. Close collaboration with stakeholders and engineering teams is essential to transform business requirements into scalable, secure, and efficient architectures.

Key Responsibilities

• Create and maintain conceptual, logical, and physical data models, ensuring adherence to standards and accuracy.
• Design master and reference data management frameworks, metadata management, and end-to-end data lineage.
• Serve as an authority for solution architecture reviews and design governance.
• Architect cloud and hybrid data solutions, including migration strategies.
• Develop scalable and secure data platform solutions leveraging Snowflake, SQL Server, and cloud-native services.
• Collaborate to translate business and analytics needs into efficient architectures, defining storage and lifecycle management strategies.
• Assess existing data ecosystems to identify gaps, technical debt, and modernization opportunities.
• Lead development of comprehensive solution blueprints, including High-Level and Low-Level Designs, engaging with both business and technical teams.
• Maintain enterprise architecture documentation using tools such as Bizzdesign, ArchiMate, and erwin Data Modeler.
• Oversee architecture governance and conduct deployment reviews to ensure compliance with standards of scalability, security, and reliability.
• Provide expert design and development for Microsoft SSIS-based ETL solutions using metadata-driven frameworks and optimizing performance.
• Define performance standards, service levels, and key metrics for data platforms, APIs, and integration services.
• Drive performance engineering and capacity planning efforts, including baseline establishment, workload analysis, and bottleneck resolution.
• Optimize queries, indexing, caching, and other components to ensure cost-effective scalability and resource utilization.
• Implement performance testing and continuous monitoring to maintain platform health and anticipate capacity needs.
• Collaborate with infrastructure and DevOps teams to enhance deployment strategies and platform reliability.
• Design and govern high availability and disaster recovery architectures to guarantee business continuity.
• Establish standards for database replication, clustering, failovers, backups, and recovery strategies in cloud and on-premise setups.
• Evaluate and optimize technologies for meeting recovery objectives, including SQL Server Always On and cloud-native solutions.
• Plan resilience testing through periodic failover and business continuity drills.
• Implement governance, security, and compliance measures, including role-based access, encryption, and data masking aligned with frameworks like DAMA-DMBOK and PDPL.
• Set up real-time monitoring using tools such as Prometheus, Grafana, and cloud monitoring services to ensure platform observability.
• Support data scientists and business users in self-service analytics and data product development through effective collaboration and documentation.
• Stay abreast of emerging data and cloud technologies to promote innovation and recommend improvements enhancing performance and cost-effectiveness.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Information Systems, or related disciplines.
• Minimum of 10 years experience in data engineering, platform architecture, or analytics engineering roles.
• Expertise with Microsoft SQL Server, SSIS, Oracle SSIS, IBM AppConnect APIs, IBM MQ, and Elasticsearch.
• Strong abilities in SQL, Python scripting, and shell scripting.
• Experience crafting robust data transformation pipelines using modern platforms.
• Familiarity with data governance standards such as DAMA-DMBOK, security policies, and data privacy laws.
• Knowledge of CI/CD pipelines and Git version control systems.
• Excellent interpersonal, communication, and leadership skills for mentoring and leading technical initiatives.