Senior Data Analyst

Bayut & dubizzle have the unique distinction of being iconic, homegrown brands with a strong presence across the seven emirates in the UAE. Connecting millions of users across the country, we are committed to delivering the best online search experience.

As part of Dubizzle Group, we are alongside some of the strongest classified brands in the market. With a collective strength of 5 brands, we have more than 123 million monthly users that trust in our dedication to providing them with the best platform for their needs.

As a Senior Data Analyst, you will be in a central position, evangelising data and our methodologies to other functional analysts and stakeholders across the company. You will have close interaction with teams in marketing, sales, finance, and product.

In this role, you will:

• Access data, construct, and manipulate large datasets to support planned analyses using SQL, Python, and similar tools.
• Design and develop BI dashboards with Sisense or similar tools (Tableau, Power BI, Data Studio) for various organisational metrics and indicators, applying best practices and industry standards across finance, sales, inventory, and other areas.
• Conduct full lifecycle analysis to include requirements, activities and design.
• Define KPIs and metrics, and drive data governance through standardisation and communication.
• Create the documentation and presentation for the management.
• Develop analysis and reporting capabilities; monitor performance and quality control plans to identify improvements.
• Adept at queries, report writing and presenting findings.
• Research and validate entity data using appropriate internal and external data sources.
• Validate entity reference data in a central account database.
• Responsible for exception management, reconciliation, and reporting.
• Liaise and perform analysis across projects within the Reference Data environment.
• Analyse, identify specifications, test, and implement interfaces, workflow solutions, and reference data solutions – for example, regression testing systems ahead of upgrades.
• Take ownership of allocated work throughout its entire life cycle.
• Develop new models to address business needs and identify and implement improvements to existing solutions; projects are diverse and can take several forms (e.g., simulation, linear/non-linear optimisation, prediction, machine learning).
• Participate in the design, implementation, and interpretation of experiments and trials to continuously refine ongoing strategies.
• Responsible for data quality and the timely delivery of reports that make common business sense.
• Create and maintain documentation for analytics, tools, and processes to ensure effective transition to the end user.
• Prepare and deliver Data Analytics & Reporting training to evangelise data across the organisation.
• Be able to work autonomously without supervision on complex projects.