Data Analyst (AI focused)

JOB PURPOSE:

The Data Analyst supports the AI and Digital teams by collecting, preparing, analysing, and interpreting data to drive intelligent automation, business insights, and data-driven decision-making. This role plays a critical part in transforming raw data into meaningful insights by building reliable data pipelines, ensuring high data quality, creating visual reports, and collaborating closely with AI engineers and business stakeholders. The Data Analyst helps improve model performance, operational efficiency, and strategic outcomes through accurate and actionable data analysis.

KEY ACCOUNTABILITIES:

• Collect, clean, transform, and manage structured and unstructured data to support AI, analytics, and business intelligence initiatives.
• Develop and maintain data pipelines, warehouses, and models using SQL, Azure Data Lake, and Power BI to ensure accuracy, consistency, and scalability.
• Collaborate with cross-functional teams including IT, Finance, business to deliver high-quality analytical outputs.
• Collaborate closely with AI Engineers to prepare and validate datasets for machine learning (ML) and large language model (LLM) training, fine-tuning, and evaluation.
• Write and optimize complex SQL queries to extract, analyse, and validate large datasets from multiple enterprise systems.
• Build and maintain Power BI dashboards, interactive visualizations, and executive reports, enabling stakeholders to monitor KPIs and derive actionable insights.
• Define, measure, and track key performance indicators (KPIs) related to data quality, automation efficiency, and AI model performance.
• Conduct trend analyses and root cause investigations to identify patterns, business opportunities, and areas for performance improvement.
• Support data workflow automation using tools such as Power Automate, n8n, or Python scripts, improving data processing efficiency and reliability.
• Monitor and validate data quality, consistency, and completeness across operational and analytical systems.
• Prepare comprehensive documentation of data sources, transformations, and business definitions for transparency and governance.
• Ensure adherence to data governance, security, and privacy standards in line with organizational policies and UAE compliance regulations.
• Provide end-user support by responding to data-related queries and incidents through ticketing systems or email, ensuring resolution within SLA and customer satisfaction benchmarks.

EXPERIENCE & QUALIFICATION

• Minimum Qualification: Bachelor’s degree in computer science/ engineering/ Information Systems, or related field
• Minimum Experience: 2+ years in similar role

SKILLS, KNOWLEDGE & ABILITIES:

• Strong hands-on expertise in SQL for complex querying, data extraction, aggregation, and performance optimization across large datasets.
• Proven experience with Power BI, including data modeling, DAX measures, calculated columns, and building high-performance, business-ready dashboards.
• Proficiency in SQL, Python, or R for data analysis and manipulation.
• Familiarity with cloud platforms (AWS, Azure, GCP) and big data tools is a plus.
• Solid capability in data cleaning, transformation, and preparation to support analytics, reporting, and AI/ML use cases.
• Experience working with enterprise data sources such as ERP, WMS, Transport Management Systems, CRM, POS Applications, e-commerce, and operational systems.
• Good understanding of data warehousing concepts, including fact/dimension models, KPIs, and performance measurement.
• Familiarity with Azure data platforms (e.g., Azure Data Lake) and the broader Microsoft analytics ecosystem,
• Ability to translate business requirements into analytical solutions, delivering insights with minimal supervision.
• Strong analytical thinking to identify trends, anomalies, data gaps, and improvement opportunities, including support for AI model monitoring.
• Experience with data workflow automation and operational support, including handling user queries, incidents, and SLA-driven requests.

Generic Skills

• Excellent listening, communication, interpersonal and presentation skills
• Domain and Business knowledge
• Ability to approach data and situations logically
• Drive to meet and exceed goals, and standards of excellence
• Ability to contribute both independently and as part of a team