Solution Architect at Datamatics Global Services Ltd

Datamatics Global Services Ltd; Riyadh; On-site; SAR 280,000 - 480,000; Full time

Job summary

Datamatics Global Services Ltd. seeks an experienced Solution Architect to design and govern enterprise data solutions on-premises, cloud, and hybrid platforms.

You will lead data modeling, metadata management, and end-to-end data pipelines, collaborating with stakeholders to translate business needs into scalable architectures. The role requires 10+ years of enterprise data experience, strong SQL, Python, and scripting skills, and hands-on work with SQL Server, SSIS, IBM AppConnect, and IBM MQ.

Qualifications

• 10+ years of experience in data engineering, data platform, or analytics engineering roles.
• Proficient in SQL Server, SSIS, Oracle SSIS, IBM AppConnect APIs, IBM MQ and Elasticsearch.
• Strong SQL, Python, and shell scripting capabilities.
• Familiar with data governance frameworks (e.g., DAMA‑DMBOK), security, and data privacy regulations.
• Knowledge of CI/CD practices and Git-based version control.

Responsibilities

• Design, govern, and optimize enterprise data platform architectures across on-premises, cloud, and hybrid environments.
• Lead data modeling, metadata management, and data lineage initiatives.
• Architect end-to-end data pipelines and ETL with SSIS, SQL Server, Snowflake, and cloud services.
• Ensure HA/DR, security governance, and performance optimization across platforms.
• Collaborate with stakeholders and lead architecture reviews.

Skills

SQL

Python

Shell scripting

Education

CS/IS degree

Tools

SQL Server

SSIS

Oracle SSIS

IBM AppConnect

IBM MQ

Elasticsearch

Job description

Job Title: Solution Architect

Experience: 10+ Years (Mandatory)

Location: Riyadh - Onsite

Employment Type: Full-Time

Overview: We are seeking an experienced and strategic Solution Architect to join our team onsite in the Kingdom region. The ideal candidate will possess 10+ years of experience in Enterprise Solution Architecture, Data Platform Engineering, System Integration, and modern Data Ecosystems across on-premises, cloud, and hybrid environments. The Solution Architect will be responsible for designing, governing, and optimizing enterprise-wide technology solutions that align with business objectives, architectural standards, and industry best practices. This role requires close collaboration with business stakeholders, product owners, and engineering teams to translate business requirements into scalable, secure, and high-performance solution architectures. The successful candidate will have deep expertise in Microsoft SQL Server, SSIS, Oracle Database, OCI Cloud, IBM App Connect Enterprise (ACE), microservices architecture, enterprise integration, data modeling, and Enterprise Architecture practices, with hands‑on experience using architecture modeling tools such as erwin Data Modeler/Evolve, Bizzdesign, ArchiMate, and related Enterprise Architecture platforms.

This Full time on site position offers great opportunities for career growth.

Responsibilities:

Data Modeling:

• Design, Develop and maintain conceptual, logical, and physical data models for the data blueprints.
• Implement and enforce data modeling standards to ensure consistency and accuracy across the data stores and platforms.
• Design Master & Reference Data Management strategies.
• Implement Metadata Management and end-to-end Data Lineage.
• Act as Solution Architecture Review & Design Authority.
• Design Cloud & Hybrid Data Architecture and migration strategies.

Data Platform Architecture & Engineering:

• Design and implement robust, scalable, and secure data platform solutions using Snowflake, SQL Server, and cloud-native services.
• Collaborate with stakeholders to translate business and analytics needs into efficient data platform architecture.
• Define and implement data storage, access, and lifecycle management strategies across structured and semi-structured data.

Data Pipeline Development & Orchestration:

Review the existing enterprise data ecosystem to identify architectural gaps, technical debt, scalability limitations, and opportunities for modernization and continuous improvement.

• Architect end‑to‑end enterprise solutions by collaborating with business and technical stakeholders to translate business requirements into solution blueprints, feasibility assessments, High-Level Designs (HLDs), and Low-Level Designs (LLDs).
• Develop and maintain enterprise architecture artifacts using industry-standard tools such as Bizzdesign, ArchiMate, erwin Data Modeler/Evolve*, and other Enterprise Architecture modeling platforms.
• Lead architecture governance by conducting solution, implementation, and deployment reviews to ensure alignment with enterprise architecture standards, scalability, security, reliability, and operational excellence.
• Serve as the subject matter expert for Microsoft SSIS, designing and developing enterprise‑grade ETL solutions utilizing metadata‑driven frameworks, CDC/SCD implementations, complex transformations, Script Components, parallel processing, enterprise logging, deployment automation, and performance optimization.
• Define enterprise performance standards, Service Level Objectives (SLOs), and Key Performance Indicators (KPIs) for data platforms, ETL pipelines, databases, APIs, and integration services.
• Lead performance engineering and capacity planning initiatives by establishing performance baselines, conducting workload analysis, identifying bottlenecks, and implementing optimization strategies across ETL pipelines, SQL workloads, cloud services, APIs, and databases.
• Optimize platform performance through query tuning, indexing, partitioning, caching, resource governance, and pipeline optimization while ensuring scalability, reliability, cost efficiency, and optimal resource utilization.
• Establish performance testing methodologies and continuous monitoring frameworks to proactively assess platform health, predict capacity requirements, and ensure sustained operational excellence.
• Collaborate with engineering, infrastructure, and DevOps teams to continuously enhance platform performance, deployment strategies, and solution reliability while balancing business requirements, scalability, and operational costs.

High Availability, Disaster Recovery & Resilience:

• Design, implement, and govern High Availability (HA) and Disaster Recovery (DR) architectures to ensure business continuity and platform resilience.
• Define enterprise standards for database replication, clustering, failover mechanisms, backup, and recovery strategies across cloud and on-premises environments.
• Evaluate and optimize SQL Server Always On Availability Groups, replication technologies, and cloud-native HA solutions to meet Recovery Time Objectives (RTO) and Recovery Point Objectives (RPO).
• Establish resilience testing frameworks by conducting periodic failover, disaster recovery, and business continuity exercises to validate platform readiness.
• Collaborate with infrastructure and operations teams to continuously improve system availability, reliability, and fault tolerance.

Governance, Security & Compliance:

• Implement role‑based access control, encryption, and data masking in compliance with data governance standards.
• Partner with security teams to ensure the platform aligns with enterprise compliance and audit requirements.
• Define and enforce Data Governance aligned with DAMA‑DMBOK, NDMO, SDAIA and PDPL.

Platform Monitoring & Observability:

• Set up and maintain real‑time monitoring using tools such as Prometheus, Grafana, and native cloud monitoring tools.
• Provide transparency into data jobs, pipeline statuses, and platform health.

Collaboration & Enablement:

• Partner with data scientists, analysts, and business stakeholders to support self‑service analytics and data product development.
• Document architecture, data flow, and technical decisions using industry best practices.

Technology Innovation & Evaluation:

• Continuously monitor and evaluate emerging technologies, trends, and best practices within the data and cloud ecosystem.
• Evaluate new tools and recommend integration to enhance platform scalability, performance, and cost-effectiveness.

Qualifications:

• Bachelor’s or Master’s in Computer Science, Information Systems, or a related field.
• 10+ years of experience in data engineering, data platform, or analytics engineering roles.
• Proficient in SQL Server, SSIS, Oracle SSIS, IBM AppConnect APIs, IBM MQ and Elastic Search.
• Strong SQL, Python, and shell scripting capabilities.
• Experience building data transformation pipelines using modern technologies and platforms.
• Familiar with data governance frameworks (e.g., DAMA‑DMBOK), security, and data privacy regulations.
• Knowledge of CI/CD practices and Git-based version control.
• Excellent communication and collaboration skills.
• Comfortable leading initiatives and mentoring colleagues and team members.