Senior Data Quality Engineer

Description & Requirements

• At Emirates Group our Analytics Centre of Excellence (ACoE) is a centralized unit that provides data and analytics support to Emirates Group businesses. This allows our businesses to make better decisions by using data and analytics to understand our customers, operations, and markets. The ACoE is an essential part of Emirates Group's digital transformation strategy. The unit is helping Emirates Group to become a more data-driven organization and to make better decisions by using data and analytics.
• As a Senior Data Quality & Automation Engineer you will be a fully participating member of a cross-functional team working autonomously on technology development and problem resolution in the Enterprise Data & Analytics space. The role involves hands on contributing to quality practices along with designing and implementing data quality and automation platforms. They will also provide support to technical analytics solutions and products that support Emirates Airlines and the Emirates Group businesses.
• In this role you will:
• Work closely with product owners, analysts, software engineers and architects to understand the technical landscape and context of deliveries to refine complex functional and non-functional requirements and translate it into fit for purpose acceptance tests.
• Work on problems of diverse scope where analysis of data requires evaluation of identifiable factors and select methods to validate and automate the solution.
• Build test strategies and test plans validating the core business problem and translating them into tests around code functionality, data quality, performance, and security.
• Build and support generating or mocking of test data for exploratory analysis and running tests.
• Design and build automated tests / jobs of moderate to high scope and complexity across all stages of the data pipeline while demonstrating good coding & design practices and adhering to published coding standards and guidelines.
• Build and enhance data quality rules and platforms for observability across the data pipeline
• Debug complex issues, resolve blockers and follow design documents with minimal or no supervision.
• Conduct data analysis activities such as source system analysis, data modelling, data dictionary collection, data profiling and source-to-target mapping ensuring delivery on business needs.