DATA ENGINEER – DATA ANALYTICS, FRAUD ANALYTICS & BUSINESS INTELLIGENCE

Location: Egypt or Jordan – Remote

Headcount: 3 Openings

Experience Required:

• 2 Openings: 3–4 Years of Experience
• 1 Opening: 5–8 Years of Experience

Engagement: Contract / Freelance

Key Responsibilities

• Collect, process, analyze, and interpret large volumes of structured and unstructured data to support business intelligence, fraud analytics, operational reporting, and data-driven decision-making.
• Develop and maintain Business Intelligence (BI) dashboards, analytical reports, KPI monitoring solutions, and interactive data visualizations to provide actionable business insights.
• Perform Fraud Analytics, Anomaly Detection, Suspicious Activity Analysis, and Pattern Identification to support the identification of potential fraudulent activities, unusual transactions, and operational irregularities.
• Utilize Microsoft-based analytics technologies, including Power BI, SQL Server, and relevant Microsoft data platforms, to develop scalable reporting and analytics solutions.
• Write, optimize, and maintain SQL queries, stored procedures, database scripts, and analytical datasets for data extraction, transformation, validation, and reporting.
• Apply Data Science, Statistical Analysis, Predictive Analytics, and Exploratory Data Analysis (EDA) techniques to identify trends, patterns, correlations, and potential business risks.
• Design, develop, and enhance Power BI dashboards, including data modelling, DAX calculations, Power Query transformations, and interactive reporting features.
• Support Data Engineering activities, including data extraction, ETL/ELT processes, data integration, data transformation, and data pipeline development.
• Work with data from multiple business systems, operational databases, transactional platforms, and enterprise applications to ensure accurate and consistent analytical reporting.
• Perform data cleansing, validation, reconciliation, and quality assurance to maintain reliable datasets and accurate business intelligence outputs.
• Develop and maintain analytical models to support fraud detection, operational performance monitoring, customer behavior analysis, and business forecasting.
• Collaborate with business analysts, data engineers, data scientists, and technical stakeholders to translate business requirements into analytical solutions.
• Support the integration of data from various sources into centralized reporting platforms, data warehouses, and analytical environments.
• Identify opportunities to automate recurring reports, data preparation activities, dashboard updates, and analytical workflows.
• Investigate data inconsistencies, reporting discrepancies, unusual patterns, and potential data quality issues, recommending appropriate corrective actions.
• Support analytics initiatives within the Utilities Industry, including operational performance reporting, consumption analysis, billing analytics, revenue assurance, and potential fraud detection.
• Prepare analytical reports, technical documentation, dashboard specifications, and data analysis findings for business and technical stakeholders.
• Communicate complex analytical findings through clear visualizations, reports, presentations, and actionable recommendations.
• Work independently in a remote consulting environment, coordinating with project teams and stakeholders to deliver analytical requirements within agreed timelines.

Experience & Professional Qualifications

• 3–4 years of relevant experience for the 2 mid-level openings, or 5–8 years for the senior opening, across Data Analytics, Business Intelligence, Data Science, Data Engineering, or related disciplines.
• Strong hands-on experience in Data Analytics, Business Intelligence, Fraud Analytics, Dashboard Development, and Microsoft-based Data Technologies.
• Proven experience developing BI dashboards, operational reports, KPI visualizations, and analytical reporting solutions.
• Strong proficiency in SQL, including data extraction, complex queries, joins, aggregations, data transformation, and query optimization.
• Practical experience with Microsoft Power BI, including Power Query, DAX, data modelling, dashboard development, and report publishing.
• Experience with Microsoft SQL Server, Azure SQL, Microsoft Fabric, Azure Synapse Analytics, or similar Microsoft data technologies is advantageous.
• Knowledge of Fraud Analytics, Fraud Detection, Anomaly Detection, Risk Analytics, and Suspicious Pattern Identification.
• Understanding of Data Science concepts, Statistical Analysis, Predictive Modelling, Exploratory Data Analysis, and Data Visualization.
• Experience using Python, particularly Pandas, NumPy, Scikit-learn, or similar data analysis libraries, is advantageous.
• Familiarity with ETL/ELT processes, Data Pipelines, Data Integration, Data Warehousing, and Data Transformation.
• Hands-on experience with Azure Data Factory, SQL Server Integration Services (SSIS), Microsoft Fabric Data Pipelines, or equivalent data engineering tools is advantageous.
• Good understanding of Data Modelling, Relational Databases, Data Quality, Data Governance, and Reporting Architecture.
• Experience integrating data from multiple sources, including relational databases, APIs, Excel files, enterprise applications, and cloud-based platforms.
• Ability to develop and maintain automated reporting solutions, analytical workflows, and reusable datasets.
• Knowledge of Machine Learning, Predictive Analytics, Classification Models, and Anomaly Detection Algorithms is advantageous.
• Experience working with large datasets, identifying data trends, resolving inconsistencies, and translating findings into business recommendations.
• Utilities, Energy, Electricity, Water, Telecommunications, or similar industry experience is advantageous, particularly exposure to billing analytics, consumption analysis, revenue assurance, or fraud detection.
• Experience supporting consulting engagements, enterprise analytics projects, or client-facing data initiatives is beneficial.
• Strong analytical thinking, problem-solving, data interpretation, troubleshooting, and technical documentation skills.
• Excellent communication and stakeholder management skills, with the ability to present analytical findings to technical and non-technical audiences.
• Ability to work independently in a fully remote environment, manage multiple deliverables, and collaborate effectively with distributed project teams.
• Candidates must be based in Egypt or Jordan and available to start in late December 2026 or early January 2027.
• Bachelor's degree in Computer Science, Data Science, Information Technology, Statistics, Mathematics, Engineering, or a related field is preferred.
• Relevant certifications such as Microsoft Certified: Power BI Data Analyst Associate (PL-300), Microsoft Fabric Analytics Engineer Associate (DP-600), Azure Data Engineer Associate, or equivalent data analytics certifications are advantageous.