Enterprise Data Architect

Summary Introduction:

Enterprise data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles. The data architect is responsible for visualizing and designing an organization's enterprise data management framework. This framework describes the processes used to plan, specify, enable, create, acquire, maintain, use, archive, retrieve, control, and purge data. The data architect also "provides a standard common business vocabulary, expresses strategic requirements, outlines high-level integrated designs to meet those requirements, and aligns with enterprise strategy and related business architecture.

Responsibilities

• Facilitate the establishment and execution of the roadmap and vision for information delivery and management, including the enterprise data warehouse, big data, BI & analytics, content management and data management

• Translating business requirements into technical specifications, including data streams, integrations, transformations, databases, and data warehouses

• Work with data engineers to architect and deliver the solutions that fulfill the Business information needs and align with the information vision and strategy

• Apply business strategy while driving technology strategy, balancing short term and long term needs to ensure that the architecture can scale and evolve accordingly

• Engage an end-to-end approach by connecting all the pieces of data to deliver the data while leveraging all available assets

• Provide advice, guidance, direction, and authorization to carry out major plans and procedures to ensure schedule attainment, product development process adherence, and performance and budget targets are met

• Take an active role in the performance management process by completing goal setting, interim review, and year-end review on a timely basis and soliciting ongoing feedback

• Defining the data architecture framework, standards and principles, including modeling, metadata, security, reference data such as product codes and client categories, and master data such as clients, vendors, materials, and employees

• Defining various data architecture artifacts like conceptual data model,logical data model, physical data model , integration catalogues and so on.

• Defining reference architecture, which is a pattern that others can follow to create and improve data systems

• Defining data flows, i.e., which parts of the organization generate data, which require data to function, how data flows are managed, and how data changes in transition

• Collaborating and coordinating with multiple departments, stakeholders, partners, and external vendors

Requirements:

• 5-8 years of experience in data architecture domain

• Strong expertise in assessing the current state of data architecture, identifying gaps, and addressing key challenges.

• Proven ability to gather and translate business requirements into effective data architecture designs.

• Extensive experience in developing reference data architecture frameworks.

• Skilled in documenting both current-state and target-state data architectures.

• Well-versed in selecting appropriate data principles, industry trends, and standards to guide architecture decisions.

• Experienced in choosing suitable content metamodels to align with business and data needs.

• Broad knowledge of data integration technologies, patterns, and best practices.

• Hands-on experience with data processing tools (ETL/ELT) and modern storage solutions such as data lakes and lakehouses.

• Proficient in data modeling using tools like ERwin and ARIS.

• Strong background in business process modeling and alignment with enterprise strategies.

• Solid understanding of Saudi Arabia’s national regulatory requirements (NDI, NDMO, QIYAS, NORA) and the practical know-how to ensure compliance.

• Advanced SQL skills with experience in relational databases and distributed database systems like SingleStore and Vitess.

• Experience with a range of NoSQL databases, including Cassandra, MongoDB, Neo4j, Elasticsearch, and the ELK Stack.

• Bachelor's degree in Computer Science/Information System.

• English and Arabic language.