Data Engineer
JOB DETAILS: Position Title: Data Engineer Reports to: Data and AI Manager Business Line/ Department: Data and Automation/it 3.
JOB PURPOSE: The Job Holder is Responsible to Builds and maintains data pipelines, ETL/ELT processes, and data integration solutions that move and transform data across the data platform to support analytics, reporting, and AI applications.
4. Job Deliverables - Accountability Description Deliverables Pipeline Success Rate ≥99% Data Freshness SLA Meets agreed refresh schedule Data Quality Score ≥95% Pipeline Documentation 100% Incident Response ≤2 hours for pipeline failures 5.
Know How (applying of knowledge & skills in job tasks) Description Data Pipeline Development • Design, build, and maintain ETL/ELT pipelines using Azure Data Factory, Synapse, or Databricks.
• Integrate data from D365 ERP, POS, e-commerce, and external sources into the data warehouse.
• Monitor pipeline performance and resolve data failures promptly.
Data Quality • Implement data quality checks and validation within pipelines.
• Collaborate with Data Analysts and BI Developers to resolve data issues.
• Maintain data lineage and documentation for all pipelines.
Note: The principal accountabilities listed above are an illustrative list and not an exhaustive list.
Additional responsibilities may be added from time to time depending on organizational requirements.
6. QUALIFICATIONS, EXPERIENCE: Minimum Qualification Bachelor degree in Computer Science, Data Engineering, or IT.
Certified in Azure Data Engineer Associate preferred Minimum Experience Minimum Experience of 3–5 years in data engineering.
Other Requirement (Skills Set) Azure Data Factory, Synapse Analytics, Databricks SQL, Python, Spark for data transformation D365 data integration: OData, Data Integrator, dual write Data quality and testing in pipelines Git and Azure DevOps for pipeline code management Arabic (Professional) · English (Professional)
JOB PURPOSE: The Job Holder is Responsible to Builds and maintains data pipelines, ETL/ELT processes, and data integration solutions that move and transform data across the data platform to support analytics, reporting, and AI applications.
4. Job Deliverables - Accountability Description Deliverables Pipeline Success Rate ≥99% Data Freshness SLA Meets agreed refresh schedule Data Quality Score ≥95% Pipeline Documentation 100% Incident Response ≤2 hours for pipeline failures 5.
Know How (applying of knowledge & skills in job tasks) Description Data Pipeline Development • Design, build, and maintain ETL/ELT pipelines using Azure Data Factory, Synapse, or Databricks.
• Integrate data from D365 ERP, POS, e-commerce, and external sources into the data warehouse.
• Monitor pipeline performance and resolve data failures promptly.
Data Quality • Implement data quality checks and validation within pipelines.
• Collaborate with Data Analysts and BI Developers to resolve data issues.
• Maintain data lineage and documentation for all pipelines.
Note: The principal accountabilities listed above are an illustrative list and not an exhaustive list.
Additional responsibilities may be added from time to time depending on organizational requirements.
6. QUALIFICATIONS, EXPERIENCE: Minimum Qualification Bachelor degree in Computer Science, Data Engineering, or IT.
Certified in Azure Data Engineer Associate preferred Minimum Experience Minimum Experience of 3–5 years in data engineering.
Other Requirement (Skills Set) Azure Data Factory, Synapse Analytics, Databricks SQL, Python, Spark for data transformation D365 data integration: OData, Data Integrator, dual write Data quality and testing in pipelines Git and Azure DevOps for pipeline code management Arabic (Professional) · English (Professional)