Data Architect Lead

Role Summary:

The Data Architect Lead will define and govern data architecture across enterprise digital transformation programs. The role translates business, reporting, analytics, and regulatory requirements into secure, scalable, and maintainable data solutions. Working closely with customer Data Management Offices (DMO), Enterprise Architecture teams, business stakeholders, solution architects, and delivery teams, you will establish trusted data foundations and guide implementation from discovery through production.

Key Responsibilities

1. Data Architecture & Strategy

• Assess existing data landscapes, platforms, integration patterns, and governance practices.
• Define current-state and target-state data architectures, gap assessments, and implementation roadmaps.
• Design architectures for data warehouses, lakehouses, operational data stores, master data, and analytics platforms.
• Establish architecture principles, reference patterns, and standards across projects.
• Evaluate technology options based on business needs, interoperability, performance, security, and total cost of ownership.
• Maintain a strong understanding of KSA NDMO policies.

2. Discovery & Data Modeling

• Lead workshops to identify data requirements, sources, owners, dependencies, and readiness gaps.
• Develop conceptual, logical, and physical data models, including shared business entities and relationships.
• Define authoritative sources, common identifiers, reference data, and reconciliation approaches.
• Review business requirements and service journeys to identify the data capabilities needed for implementation.
• Maintain traceability between business requirements, data models, source mappings, and technical designs.

3. Data Integration & Engineering

• Define patterns for batch and real-time integration, ETL/ELT pipelines, APIs, change data capture, and event-driven data flows.
• Guide source-to-target mapping, transformation rules, orchestration, and error handling.
• Design for performance, scalability, availability, recovery, and operational monitoring.
• Work with engineering teams to resolve architectural issues and review implementation quality.
• Plan data migration, reconciliation, and validation activities.

4. Governance, Quality & Security

• Collaborate with customer DMO and governance teams on metadata, cataloging, lineage, ownership, and data classification.
• Define data quality rules, controls, monitoring, and remediation responsibilities.
• Incorporate access controls, encryption, retention, privacy, and residency requirements into solution designs.
• Align architecture with applicable customer policies and regulatory requirements.
• Support the development of reusable data definitions and business glossaries.

5. Technical Leadership & Delivery

• Lead and mentor data architects and engineers across delivery teams.
• Coordinate data dependencies with business analysis, integration, application, analytics, and infrastructure leads.
• Review designs, estimates, implementation plans, and architecture decisions.
• Identify and communicate data-related risks, assumptions, and constraints early.
• Support testing, deployment readiness, operational handover, and production issue resolution.
• Present architecture recommendations and explain trade-offs to technical and business audiences.
• Define scope boundaries, prerequisites, dependencies, and acceptance criteria for data deliverables.
• Build trusted working relationships with customer architecture and data leadership teams.

Required Qualifications & Experience

• Education: Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field.
• Experience: 10+ years of relevant experience, including 5+ years in data architecture and demonstrated technical leadership.
• Proven experience designing and delivering enterprise data platforms involving multiple source systems and stakeholder groups.
• Strong expertise in data modeling, SQL, relational databases, dimensional modeling, and warehouse/lakehouse architectures.
• Experience with ETL/ELT, data integration, migration, orchestration, and reconciliation.
• Practical understanding of master data management, metadata, lineage, and data quality.
• Experience with cloud or hybrid data environments using Microsoft Azure, AWS, or Google Cloud.
• Ability to produce clear architecture diagrams, data models, specifications, and decision records.
• Strong customer-facing communication, workshop facilitation, and stakeholder management skills.
• Language: Professional proficiency in Arabic and English.

Preferred Qualifications

• Experience delivering programs for government entities, regulators, banks, capital market institutions, or investment firms.
• Experience working with Saudi Arabian or wider GCC clients.
• Familiarity with Saudi data management and privacy requirements, including relevant NDMO standards and PDPL considerations.
• Hands-on experience with Microsoft Fabric, Azure Data Factory, Azure Databricks, Snowflake, or equivalent platforms.
• Exposure to analytics and reporting platforms such as Incorta, Power BI, or Qlik.
• Experience establishing shared data foundations for enterprise applications, regulatory reporting, or Customer/Company 360 solutions.
• Understanding of data foundations for AI and advanced analytics.
• Relevant certifications in data architecture, cloud architecture, Microsoft Fabric, Snowflake, TOGAF, or DAMA.

What Success Looks Like

• Clear, approved data architectures that support business and delivery objectives.
• Early identification of data readiness gaps and integration dependencies.
• Consistent data definitions, models, and ownership across workstreams.
• Reliable pipelines and measurable improvements in data quality.
• Secure, maintainable solutions supported by effective documentation and operational handover.