Azure Cloud Solution Architect

Legacy Data Migration | AI Data Platforms | API & Integration | Secure by Design

Location: Kuwait, on-site at client premises with hybrid flexibility

Experience: 8+ years in enterprise architecture/data engineering, including 4+ years on Azure

Reports to: Solution Architect & Delivery Lead

Certification: Azure Solutions Architect Expert, AZ-305, required or to be attained within 6 months

Languages: Fluent English required; working Arabic strongly preferred

Travel: Occasional GCC travel for discovery and assessment workshops

Role Overview

We are looking for an Azure Cloud Solution Architect to lead complex legacy modernization, data migration, AI data platform, API, integration, and secure cloud architecture engagements for public sector and regulated enterprise clients.

The role focuses on moving clients from legacy estates, including IBM i / AS/400, DB2 for i, Oracle, DB2 LUW, batch interfaces, spreadsheets, and fragmented systems, into secure, governed, cloud-based platforms on Microsoft Azure.

This is not a lift-and-shift role. The architect will define the target state, migration path, integration architecture, data governance foundation, AI enablement approach, and security posture. The role requires hands-on architecture ownership from discovery through build, cutover, reconciliation, and executive-level client engagement.

Key Responsibilities

- Assess complex legacy estates including IBM i / AS/400, Oracle, DB2, batch jobs, interfaces, data volumes, dependencies, and business-critical workloads.
- Design migration strategies to Azure SQL, SQL Managed Instance, PostgreSQL, MySQL, Cosmos DB, Microsoft Fabric, Synapse, Databricks, and lakehouse platforms.
- Define rehost, replatform, refactor, retire, or wrap decisions for legacy components.
- Address complex migration challenges such as DDS files, packed/zoned decimals, EBCDIC and CCSID conversion, Arabic character handling, implicit business rules, multi-member files, and identity reseeding.
- Design reconciliation, audit, and proving strategies including row counts, aggregate checks, hashes, business-key validation, and sign-off evidence.
- Own cutover planning including dual-run, parallel-run, freeze windows, rollback, fallback, and reverse-replication approaches.
- Architect CDC and real-time data movement from IBM i journals, Oracle redo logs, DB2 logs, and other enterprise sources.
- Evaluate and select appropriate CDC and replication tools such as Qlik Replicate, IBM InfoSphere Data Replication, Oracle GoldenGate, Debezium, Kafka Connect, Azure Data Factory, Fabric CDC, and SQL CDC.
- Design eventing and streaming architectures using Azure Event Hubs, Service Bus, Event Grid, Kafka-compatible patterns, and layered data zones.
- Build governed data platforms using Azure Data Lake Storage, Databricks, Synapse, Microsoft Fabric, Delta or Iceberg formats, and medallion-style architecture.




- Establish data governance foundations including catalogue, classification, lineage, ownership, retention, and data quality using Microsoft Purview or equivalent.
- Architect AI-on-enterprise-data solutions using Azure AI Foundry, Azure OpenAI, Azure AI Search, vector and hybrid retrieval, and Document Intelligence.
- Design secure RAG solutions with chunking, embeddings, index refresh, document and row-level security, grounding, citations, evaluation, and hallucination controls.
- Support Arabic-language AI and document extraction requirements, including scanned and mixed-script sources.
- Apply process mining and workflow discovery using tools such as Celonis, SAP Signavio, UiPath Process Mining, or Microsoft Power Automate Process Mining.
- Extract event logs from legacy systems, journals, audit tables, application logs, and document systems to identify process variants, bottlenecks, rework, and automation opportunities.
- Design API and integration architectures using Azure API Management, Apigee, Kong, MuleSoft, SOAP, SFTP, message queues, legacy formats, and government service buses.
- Define API standards including OpenAPI-first design, versioning, contract testing, CI linting, error models, backward compatibility, and governance.
- Own API security including OAuth 2.0, OpenID Connect, Entra ID, JWT validation, mTLS, client certificates, scopes, rate limits, private endpoints, and WAF.
- Design secure-by-default Azure architectures aligned to Microsoft Cloud Adoption Framework, Well-Architected Framework, Zero Trust, and regulatory requirements.
- Implement security patterns using private networking, managed identities, Key Vault, Managed HSM, encryption, tokenisation, Defender for Cloud, Sentinel, DAST, SAST, IaC scanning, and secret scanning.
- Apply OWASP Top 10, OWASP API Security Top 10, OWASP ASVS, OWASP LLM Top 10, CIS benchmarks, and threat modelling practices.
- Address data residency, sovereignty, legal hold, audit, regulator, and security-accreditation requirements.
- Produce current-state assessments, target architectures, transition architectures, migration wave plans, ADRs, NFRs, risk registers, and executive-ready documentation.
- Define NFRs including RPO, RTO, availability, latency, throughput, batch windows, capacity, scalability, backup, disaster recovery, and cost.
- Own Azure cost and FinOps considerations including right-sizing, reserved capacity, savings plans, licensing, Azure Hybrid Benefit, and egress.
- Use infrastructure as code, Terraform or Bicep, CI/CD, policy as code, Git workflows, observability,



and environment promotion.
- Present and defend architecture to client executives, security authorities, steering committees, engineers, and delivery teams.
- Mentor engineers and junior architects and support pre-sales, estimation, and proposal work.

Essential Requirements

- 8+ years in enterprise architecture, data engineering, platform engineering, or cloud solution architecture.
- 4+ years designing and delivering production workloads on Microsoft Azure.
- Proven delivery of large-scale legacy-to-cloud migration, preferably involving IBM i / AS/400, DB2 for i, Oracle, or DB2 LUW.
- Hands-on experience with migration assessment, reconciliation, cutover, rollback, and production recovery.
- Deep CDC experience using enterprise replication technologies and strong understanding of latency, ordering, idempotency, schema evolution, replay, and failure handling.
- Strong Azure data platform experience across Data Factory, Data Lake Storage, Databricks, Synapse, Fabric, and Azure database services.
- Production API management experience using Azure API Management, Apigee, Kong, MuleSoft, or equivalent.
- Strong security architecture experience across Entra ID, Key Vault, Defender for Cloud, private networking, secure DevOps, OWASP, SAST, DAST, and API security.
- Applied AI experience using Azure OpenAI, Azure AI Foundry, AI Search, RAG, security-trimmed retrieval, and AI evaluation.
- Robust DevOps and IaC experience using Terraform or Bicep, Git, CI/CD, and policy as code.
- Excellent architecture communication, documentation, stakeholder management, and executive presentation skills.
- Willingness to be based in Kuwait and spend significant time on client premises.

Strongly Preferred

- AZ-305, DP-203, DP-700, AZ-500, TOGAF, Apigee, Kong, or related certifications.
- Experience with GCC government, ministries, regulators, courts, or central authorities.
- Working Arabic and experience with Arabic data, search, collation, transliteration, name matching, and document extraction.
- Process mining and workflow discovery experience on real client engagements.
- RPG, COBOL, or CL literacy.
- Experience with AWS or Google Cloud alongside Azure.
- Hybrid connectivity experience including ExpressRoute, VPN, Direct Connect, or restricted-connectivity environments.
- AKS, Kubernetes, containers, and event-driven microservices.
- Microsoft Purview or enterprise catalogue implementation experience.
- Experience with sovereign, air-gapped, or highly regulated cloud deployments.

The ideal candidate is a hands-on architect who stays accountable beyond design. They can work with old systems, uncertain documentation, sensitive data, demanding stakeholders, and regulated environments. They are comfortable making pragmatic technology decisions, explaining trade-offs clearly, and balancing innovation with security, maturity, cost, and operational risk.

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