Job Description
RAKBANK is looking for a highly experienced Data Platform Architect to lead the architecture, strategy, governance, and evolution of the Bank's Enterprise Data Platform. This role is responsible for defining and governing scalable, secure, cloud-native data platforms that support analytics, AI/ML, regulatory reporting, customer intelligence, and enterprise-wide data products. You will play a critical role in shaping RAKBANK's modern data ecosystem, driving architecture decisions across Databricks Lakehouse, Azure, Kafka, Informatica, Power BI, Data Governance, and AI-ready data foundations.
What You Will Be Doing
Enterprise Data Platform Strategy & Architecture
- Define and maintain the Enterprise Data Platform target-state architecture and roadmap.
- Establish architecture standards, principles, reusable patterns, and reference architectures.
- Ensure alignment with enterprise architecture, security, compliance, and cloud strategy.
- Lead architecture decisions supporting analytics, AI/ML, reporting, and regulatory capabilities.
Platform Ownership & Governance
- Own platform architecture standards across Databricks, Delta Lake, Azure Data Factory, Confluent Kafka, Informatica/IICS, metadata, and data quality services.
- Drive platform scalability, resilience, observability, performance, and cost optimization.
- Define engineering standards, automation frameworks, CI/CD practices, and operating models.
Data Governance, Privacy & Compliance
- Embed governance, lineage, metadata, quality, retention, access control, encryption, masking, and privacy-by-design principles.
- Ensure compliance with UAE PDPL, CBUAE regulations, internal policies, and audit requirements.
- Partner closely with Data Governance, Information Security, Risk, and Compliance teams.
Integration & Streaming Architecture
- Define enterprise integration standards for batch, real-time, and event-driven architectures using Kafka, CDC, APIs, and ETL/ELT.
- Govern integration patterns across on-premises, cloud, SaaS, and partner ecosystems.
- Eliminate non-standard point-to-point integrations and uncontrolled data movement.
AI & Advanced Analytics Enablement
- Design trusted and governed foundations for AI, Machine Learning, GenAI, and advanced analytics.
- Enable reusable data products, domain data models, and AI-ready datasets.
- Ensure responsible AI principles, including explainability, lineage, privacy, and observability.
Architecture Leadership
- Review and approve platform solution designs and technology selections.
- Present architecture proposals and exceptions to Enterprise Design Authority (EDA).
- Mentor architects and engineering teams while driving strategic technology decisions.
What We Are Looking For
- 12+ years of experience across Data Architecture, Data Platform Architecture, Solution Architecture, or Enterprise Architecture.
- Minimum 5 years leading enterprise-scale data platform transformation initiatives.
- Strong experience within Banking or Financial Services environments.
- Proven delivery of Databricks-based Lakehouse architectures and AI-enabled data platforms.
- Experience establishing enterprise data governance frameworks, standards, and architecture guardrails.
- Bachelor's degree in computer science, Information Systems, Engineering, Data Science, or a related field.
- Master's Degree is preferred.
- Professional Certifications (Preferred)
- Databricks Certified Data Engineer Professional
- Databricks Solution Architect
- Microsoft Azure Solutions Architect Expert
- Azure Data Engineer Associate
- TOGAF
- CDMP
Technical Expertise
- Databricks Lakehouse, Delta Lake, Spark, PySpark, Python, SQL.
- Azure Data Factory, Confluent Kafka, CDC, Event-Driven Architecture.
- Data Mesh, Data Products, Metadata Management, Data Lineage, Data Quality.
- Azure, AWS, Hybrid Cloud Architecture, Infrastructure-as-Code, DevOps, CI/CD.
- Power BI, Semantic Models, Self-Service Analytics.
- Privacy Controls, Encryption, Tokenization, RBAC/ABAC, Zero Trust Security.
