Senior Manager, Data Engineering

Job Description

About QNBEstablished in 1964 as the country's first Qatari-owned commercial bank, QNB Group has steadily grown to become the largest bank in the Middle East and Africa (MEA) region. QNB Group's presence through its subsidiaries and associate companies extends to more than 31 countries across three continents providing a comprehensive range of advanced products and services. The total number of employees is more than 28,000 serving up to 20 million customers operating through 1,000 locations, with an ATM network of 4,300 machines. QNB has maintained its position as one of the highest rated regional banks from leading credit rating agencies including Standard & Poor's (A), Moody's (Aa3), and Fitch (A+). The Bank has also been the recipient of many awards from leading international specialized financial publications. Based on the Group's consistent strong financial performance and its expanding international presence, QNB currently ranks as the most valuable bank brand in the Middle East and Africa, according to Brand Finance Magazine. QNB Group has an active community support program and sponsors various social, educational, and sporting events.

Job Purpose Summary: The incumbent is responsible for building and maintaining the data infrastructure that enables data analysis and data science. They design, construct, test, and optimize data pipelines, databases, data warehouses, and other data systems. They also ensure data quality, reliability, and performance, through strong programming, database, and software engineering skills as well as knowledge of data architectures and frameworks.

Essential Duties & Responsibilities by Dimensions:

• Plan and monitor the implementation of development lifecycle strategies, policies, standards, and guidelines for design, selection, development, and ongoing maintenance of systems
• Contribute to data model deployment in test and production and creating data workflow automation
• Ensure proper implementation of strategies policies, standards, and guidelines of project management and control to deliver the projects assigned objectives within the limited resources, time, and budget.
• Implement test plans and scripts standards
• Monitor and recommend solutions to cater for the user business requirements and provide the most adequate systems to resolve these requirements.
• Carry out any projects or assignments as assigned by Data Scientist or Data Analysis
• Participate proactively in any new projects that require deployment or during the acquisition of new tools/technology required by the Group and follow up on the progress of ongoing projects.
• Implement and ensure readiness of all data tools or software required by the data scientist team to assist them in building analytics models.
• Implement and ensure all queries and data set are provided on time and with quality to the Data Analysis team to assist them in their analytics
• Implement automated processes and data monitoring techniques to ensure data quality, ensuring production data is accurate and available for key stakeholders
• Ensure all dev/test environment setup and configuration are delivered on time with quality.
• Recommend live operations of the systems or retirement of the system with the Group's IT architecture based on business objectives and strategy.
• Ensure compliance and adherence to existing standards and policies by all the Data Development staff and follow the most recent control objectives and best practices.
• Implement tasks according to the prioritization based on the overall business plans and other factors of limitation and urgencies.
• Ensure the enforcement of segregation of critical role as Developer and Tester, as well adherence to all data governance and quality guidelines.

Education & Experience Requirements:

• University graduate preferably with a Major in computer science, data science, software engineering, information systems, or related quantitative field.
• At least 8 years of relevant experience, preferably within a Data Engineer role.
• Experience building and optimizing data pipelines, architectures, data sets, and all its underlying environments.
• Excellent oral and written communication skills (including report writing) in English and Arabic.
• Excellent Coding knowledge, Python, Golang, Ruby, Perl, Scala, Java, SAS, R, MATLAB, C, and C++, etc.
• Excellent Data Warehouse solutions technical knowledge, such as Panoply or Redshift.
• Excellent OS administrative knowledge, MS, Linux, Solaris, UNIX, etc.
• Excellent database and relational database-related administrative knowledge, MySQL, Oracle, SQL, etc.
• Experience with data pipeline and workflow management tools (ETL, Airflow, etc.) and big data tools (Hadoop, Spark, Kafka, etc.)
• Ability to make decisions and follow through with initiatives.
• Personal integrity and self-management.

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