Data Analyst – Social Support Operations - UAE National

About the Role We are seeking a skilled Data Analyst to support Social Support Operations through data analysis, reporting, data-quality management, and business intelligence. The role will be responsible for transforming data from multiple sources into accurate, actionable insights that support operational decision-making, performance monitoring, audit, and service improvement. Key Responsibilities • Clean, transform, validate, and analyze data from multiple sources using Python, SQL, Excel, and Power BI. • Develop and maintain professional Power BI dashboards and reports, including KPIs, trends, forecasts, and interactive visualizations. • Design data models and implement DAX measures, Power Query, drill-throughs, tooltips, and row-level security. • Write and optimize complex SQL queries involving joins, subqueries, CTEs, window functions, aggregations, views, and stored procedures. • Extract and analyze data from CRM platforms, preferably Microsoft Dynamics 365. • Investigate and reconcile discrepancies across CRM systems, databases, integrations, reports, and source data. • Identify and resolve data-quality issues, including missing data, duplicates, invalid values, inconsistent classifications, and broken relationships between datasets. • Conduct trend, variance, month-over-month, and forecasting analyses. • Develop automated data-quality checks, exception reports, and validation mechanisms for operational and audit purposes. • Translate business requirements and business rules into SQL, Python, DAX, and data-validation logic. • Gather and document business and technical requirements and define KPIs, calculation rules, assumptions, filters, and acceptance criteria. • Conduct root-cause analysis of data and business-process discrepancies. • Prepare data-validation and User Acceptance Testing (UAT) cases and compare system results against expected business outcomes. • Communicate analytical findings clearly to technical and non-technical stakeholders through dashboards, reports, and presentations. • Maintain appropriate documentation covering business rules, data definitions, calculations, data-quality issues, test cases, assumptions, and limitations. • Work collaboratively with business teams, developers, auditors, finance teams, and system vendors. • Ensure data confidentiality, security, access control, auditability, and reproducibility of calculations. Required Qualifications & Experience • Bachelor's degree in Data Analytics, Computer Science, Statistics, Information Systems, Business Analytics, or a related field. • Strong hands-on experience with Python, particularly Pandas, NumPy, Matplotlib, and Seaborn. • Advanced SQL skills and experience with Microsoft SQL Server or similar relational databases. • Strong Power BI experience, including DAX, Power Query, data modelling, and dashboard development. • Advanced Microsoft Excel skills, including XLOOKUP, SUMIFS, COUNTIFS, IF/IFERROR, Pivot Tables, and Power Query. • Experience analyzing and validating data from multiple sources. • Strong understanding of data-quality principles and data reconciliation. • Experience with CRM data; Microsoft Dynamics 365 experience is preferred. • Strong analytical, problem-solving, and root-cause analysis skills. • Ability to translate complex business processes into measurable requirements and analytical solutions. • Strong communication and documentation skills. Preferred Qualifications • Microsoft Power BI or equivalent analytics certification. • Experience with Microsoft Dynamics 365 CRM. • Familiarity with Azure, Data Factory, Microsoft Fabric, APIs, or data integration technologies. • Knowledge of Git or other version-control systems. • Familiarity with Agile delivery and requirements-management practices. Key Skills Python | SQL | Power BI | DAX | Power Query | Microsoft Excel | Data Modelling | Data Quality | Data Validation | CRM Analytics | Microsoft Dynamics 365 | Business Intelligence | KPI & Reporting | Forecasting | Root-Cause Analysis | UAT | Data Governance Show more Show less

Bachelor's degree in Data Analytics, Computer Science, Statistics, Information Systems, Business Analytics, or a related field. Strong hands-on experience with Python (Pandas, NumPy, Matplotlib, Seaborn). Advanced SQL skills and experience with Microsoft SQL Server or similar relational databases. Strong Power BI experience (DAX, Power Query, data modelling, and dashboard development). Advanced Microsoft Excel skills (XLOOKUP, SUMIFS, COUNTIFS, IF/IFERROR, Pivot Tables, Power Query). Experience analyzing and validating data from multiple sources. Strong understanding of data-quality principles and data reconciliation. Experience with CRM data; Microsoft Dynamics 365 experience is preferred. Strong analytical, problem-solving, and root-cause analysis skills. Ability to translate complex business processes into measurable requirements and analytical solutions. Strong communication and documentation skills.

Clean, transform, validate, and analyze data from multiple sources using Python, SQL, Excel, and Power BI. Develop and maintain Power BI dashboards and reports, including KPIs, trends, forecasts, and interactive visualizations. Design data models and implement DAX measures, Power Query, drill-throughs, tooltips, and row-level security. Write and optimize complex SQL queries (joins, subqueries, CTEs, window functions, aggregations, views, stored procedures). Extract and analyze data from CRM platforms, preferably Microsoft Dynamics 365. Investigate and reconcile discrepancies across CRM systems, databases, integrations, reports, and source data. Identify and resolve data-quality issues (missing data, duplicates, invalid values, inconsistent classifications, broken relationships). Conduct trend, variance, month-over-month, and forecasting analyses. Develop automated data-quality checks, exception reports, and validation mechanisms for operational and audit purposes. Translate business requirements and rules into SQL, Python, DAX, and data-validation logic. Gather and document business and technical requirements and define KPIs, calculation rules, assumptions, filters, and acceptance criteria. Conduct root-cause analysis of data and business-process discrepancies. Prepare data-validation and UAT cases and compare system results against expected outcomes. Communicate analytical findings to technical and non-technical stakeholders via dashboards, reports, and presentations. Maintain documentation covering business rules, data definitions, calculations, data-quality issues, test cases, assumptions, and limitations. Collaborate with business teams, developers, auditors, finance teams, and system vendors. Ensure data confidentiality, security, access control, auditability, and reproducibility of calculations.