Data Architect – Enterprise Data & FinOps Lead

About the role

We are seeking a senior Data Architect to design and govern enterprise‑wide data solutions across SAP, Microsoft, and multiple SaaS platforms. The role combines deep technical leadership with FinOps and licensing governance to ensure cost‑effective, secure, and compliant data ecosystems.

Key responsibilities

• Develop enterprise data architecture blueprints, models, standards, and integration patterns.
• Define canonical models, master data structures, metadata, lineage, and governance principles.
• Lead data integration across SAP, Azure/Fabric, Power Platform, AWS, Google Analytics, CRM, ERP, e‑commerce and other SaaS systems.
• Provide hands‑on leadership for data warehouses, lakehouses, data marts, pipelines, semantic layers and MDM.
• Establish data governance, security, compliance, retention and access‑control frameworks.
• Enable BI, analytics, AI/ML, dashboards, predictive models and other digital use cases.
• Evaluate vendors, platforms, technologies and integration/governance tools.
• Own FinOps, licensing governance, cloud/SaaS cost optimisation, renewals and budget control.

Required profile

• Bachelor’s degree in Computer Science, Information Systems or Data Engineering (Master’s preferred).
• 15+ years of experience in data architecture, SAP/Microsoft platforms, data engineering, SaaS/on‑prem integration, analytics and cost governance.
• Mandatory certifications: at least one SAP certification and one Microsoft/Azure/Fabric certification; FinOps certification strongly preferred.
• Fluent English; Arabic is a plus.

Required skills

• SAP Stack: BW, BW/4HANA, HANA modeling, Datasphere, SAC, CDS Views, HANA Calc Views, ADSO, InfoObjects, SAP‑non‑SAP integration.
• Microsoft Stack: Azure, Fabric, Azure Data Factory, Synapse, SQL Server, SQL Database, Power BI, Power Platform, Purview, OneLake/Lakehouse, semantic models.
• Data integration patterns: API, ETL/ELT, event‑driven, batch, real‑time.
• Advanced data modeling (conceptual, logical, canonical).
• Data governance, security, metadata, lineage, compliance.
• Hands‑on data engineering: pipelines, warehouses, lakehouses, migration.
• FinOps and licensing governance across SAP, Microsoft, AWS, Google Cloud and SaaS.
• Architecture tools: ERwin, PowerDesigner, Sparx EA, Lucidchart, Visio, Draw.io.
• Digital analytics: GA4, Tag Manager, BigQuery awareness, e‑commerce and campaign analytics.