Sr. Data Architect

The Sr. Data Architect will be an integral member of the data and digital innovation team, focusing on the development, maintenance, and enhancement of the entity’s economic monitoring platform. This role requires a blend of data engineering, full stack web development, data science skills, and the ability to communicate complex analytical findings to support the entity’s mandate.

Key Responsibilities:

• Manage projects and operations relating to the development of innovative data solutions including optimal extraction, transformation, and loading of data from a wide variety of sources into data pipelines, as well as the creation and maintenance of data catalogues and architectures.
• Manage projects relating to the modernization of the entity’s data ecosystem using cloud and locally hosted solutions.
• Design and develop solutions for data-related technical problems and data infrastructure needs surfaced by Executive, Analytics and Design teams.
• Developing platforms with self-service analytics using industry standard technologies and best practices.
• Manage the identification, design, and implementation of internal process improvements i.e.: automating manual processes, optimizing data delivery, re-designing architecture for greater scalability and more innovative digital data solution creation and management.
• Deploy resources to extract data features from complex datasets for data scientists and data analysts.
• Performing data mining and extraction of large amounts of data.
• Leverage a variety of input sources (e.g., databases, flat files, vendor API's, DaaS (Data as a Service), custom applications) to populate different data solutions that drive better decision-making and prioritization within the entity.
• Any other duties as assigned by the Data and Digital Manager

Qualifications:

• Advanced university degree (master’s degree or equivalent) in computer science, information systems, statistics, applied mathematics, data management, information science or a related quantitative field.
• A minimum of five years of progressively responsible experience in data engineering, data management, data integration, data modeling, optimization, and other relevant areas is required.
• A minimum of five years of experience in designing data integration and pipeline architectures, which must include ingesting data through different methods such as message queues, database connections, flat files, REST, or specific API’s is required.
• A minimum of five years of experience developing well-organized and insightful reports, platforms, data mining, and other forms of data visualizations and data manipulation languages and tools (e.g., using Python, SQL, R, PowerBI, etc.) in support of strategic, tactical, and operational business decisions and special purposes uses is required.

Experience with distributed systems and cloud services platform with an ecosystem of data integration/quality control (e.g. ETL), data storage, processing, and visualization tools is desirable.

• A minimum of two years of experience in DevOps tool chains consisting of tools like Git, Azure DevOps, Jenkins, or Bamboo – or equivalent tools - and experience with the deployment of data pipelines is desirable.
• A minimum of two years of experience in Artificial Intelligence, particularly Machine Learning techniques for data mining and extraction of large amounts of data is desirable.
• Experience with the use of Machine Learning techniques for economic and social use cases is an advantage.
• Fluent in English and Arabic.