Skill Inventory Matrix
Enabler for Internal Mobility Program
Records
| ID | Sector | Division | Department | Unit | Technical Skills |
|---|---|---|---|---|---|
| 489 | Technology | Data & AI | Knowledge of big data infrastructure and pipeline engineering tools such as Hadoop, Spark, Kafka, Nifi, Hive, and Impala. | ||
| 490 | Technology | Data & AI | Knowledge of data governance frameworks to ensure data quality, privacy, lineage tracking, and access control across the data lifecycle. | ||
| 491 | Technology | Data & AI | Knowledge of real-time and batch data processing for high-availability platforms supporting digital banking use cases. | ||
| 492 | Technology | Data & AI | Ability to code in Python and SQL for data extraction, transformation, analysis, and model training activities. | ||
| 493 | Technology | Data & AI | Ability to lead cross-functional collaboration with engineering, UX/UI, compliance, and product teams. | ||
| 494 | Technology | Data & AI | Ability to design and implement secure and compliant data architectures, including data lakes and warehouses. | ||
| 495 | Technology | Data & AI | Ability to develop advanced data models and optimize data flows to enable predictive analytics, customer intelligence, and operational insights. | ||
| 496 | Technology | Data & AI | Data Engineering | Knowledge of data governance frameworks and ability to implement data stewardship, ownership, and classification protocols across enterprise functions. | |
| 497 | Technology | Data & AI | Data Engineering | Knowledge of master data management (MDM) practices and ability to maintain data dictionaries, business glossaries, and metadata repositories. | |
| 498 | Technology | Data & AI | Data Engineering | Knowledge of data lineage, metadata management, and impact analysis to support audit readiness and integration planning. | |
| 499 | Technology | Data & AI | Data Engineering | Knowledge of tools such as Collibra, Informatica, Talend, or Azure Purview for automating governance, metadata tracking, and quality assurance. | |
| 500 | Technology | Data & AI | Data Engineering | Ability to manage access controls and monitor tool performance to ensure automation, security, and scalability of governance processes. | |
| 501 | Technology | Data & AI | Data Engineering | Ability to enforce regulatory-compliant data privacy, access control, and retention policies in line with SAMA, NDMO, and GDPR guidelines. | |
| 502 | Technology | Data & AI | Data Products | Knowledge of big data infrastructure and tools such as Hadoop, Spark, Nifi, Kafka, Hive, and Data Lakehouse architectures for scalable data processing and integration. | |
| 503 | Technology | Data & AI | Data Products | Knowledge of data governance, privacy, and quality frameworks, including access controls and compliance with data security standards. | |
| 504 | Technology | Data & AI | Data Products | Knowledge of cloud-based data platforms and real-time processing for high-availability, cost-effective, and reliable solutions. | |
| 505 | Technology | Data & AI | Data Products | Knowledge of predictive analytics, customer behavior modeling, and market insight generation using SQL, Python, and Power BI. | |
| 506 | Technology | Data & AI | Data Products | Ability to design advanced data models and architectures that align with business requirements. | |
| 507 | Technology | Data & AI | Data Products | Ability to apply user research, journey mapping, and feedback loops to deliver intuitive and user-centric data solutions. | |
| 508 | Technology | Data & AI | Data Products | Ability to build and optimize AI and GenAI workflows using platforms like Dataiku, Azure ML, Databricks, Vertex AI, and AWS SageMaker. | |
| 509 | Technology | Data & AI | Data Products | Ability to manage data APIs, integration tools, and workflows using MS Excel, SQL, and cloud-native toolsets. | |
| 510 | Technology | Data & AI | Business Intelligence & AI | Knowledge of BI architecture, dashboard development, and performance monitoring using tools such as Power BI and enterprise reporting platforms. | |
| 511 | Technology | Data & AI | Business Intelligence & AI | Knowledge of AI/ML model lifecycle management, including feature engineering, model training, validation, deployment, and monitoring. | |
| 512 | Technology | Data & AI | Business Intelligence & AI | Knowledge of responsible AI principles including fairness, bias detection and transparency in model development. | |
| 513 | Technology | Data & AI | Business Intelligence & AI | Knowledge of statistical programming languages (e.g., Python, R), SQL, and cloud-based ML/BI tools for scalable model and dashboard deployment. | |
| 514 | Technology | Data & AI | Business Intelligence & AI | Ability to ensure regulatory compliance (SAMA, NDMO, Data Privacy) in BI and AI systems including data lineage, model governance, and access control. | |
| 515 | Technology | Data & AI | Business Intelligence & AI | Ability to apply AI techniques for use cases such as risk scoring, churn prediction, personalization, and process optimization. | |
| 516 | Technology | Data & AI | Business Intelligence & AI | Ability to optimize data lake/warehouse structures to support efficient analytics and model execution. |