✨ AI Summary
We are seeking a Data Engineer to build and maintain data pipelines, ETL/ELT processes, and data integration solutions. This role involves integrating data from various sources like D365 ERP, POS, and e-commerce into a data warehouse to support analytics, reporting, and AI applications. The Data Engineer will be responsible for ensuring pipeline success rates, data freshness SLAs, data quality scores, and prompt incident response. Key responsibilities include designing and building pipelines using Azure tools, monitoring performance, implementing data quality checks, and collaborating with other teams to resolve data issues.
Requirements
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 managementArabic (Professional) · English (Professional)
Description
JOB DETAILS:Position Title: Data EngineerReports to: Data and AI ManagerBusiness Line/ Department: Data and Automation/it3. 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 - AccountabilityDescriptionDeliverablesPipeline Success Rate ≥99%Data Freshness SLA Meets agreed refresh scheduleData Quality Score ≥95%Pipeline Documentation 100%Incident Response ≤2 hours for pipeline failures5. Know How (applying of knowledge & skills in job tasks)DescriptionData 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.