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Posted 6 days ago

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Microsoft Fabric Senior Data Engineer

Al Hay Al Asher, EGRemote

AI Summary

Designs, builds, deploys, and supports enterprise data solutions on Microsoft Fabric, owning delivery from source integration through to reliable, business-ready datasets.

About this role

Role purpose
Design, build, deploy, and support enterprise data solutions on Microsoft Fabric, owning delivery from source integration through to reliable, business-ready datasets.

Required experience and qualifications

  • 5+ years of data engineering experience, including at least 1-2 year of hands-on Microsoft Fabric implementation.

  • Proven delivery of at least one end-to-end Fabric solution running in production, including deployment and post-go-live support.

  • Active Microsoft Certified: Fabric Data Engineer Associate (DP-700) certification, supported by a verifiable credential link.

  • Relevant degree or equivalent professional experience.

Mandatory technical requirements

  • Architecture: OneLake, Lakehouse, Warehouse, Delta tables, and Bronze/Silver/Gold architecture, with the ability to explain design choices and tradeoffs.

  • Data integration: Fabric Data Factory pipelines, Dataflows Gen2, notebooks, and integration with databases, APIs, files, and enterprise applications.

  • Programming: Strong SQL/T-SQL and Python/PySpark for transformations, troubleshooting, and reusable processing logic.

  • Loading patterns: Full and incremental loads, change-data capture where supported, upserts, deduplication, schema changes, and late-arriving data.

  • Modeling and quality: Dimensional modeling, fact/dimension tables, slowly changing dimensions, validation rules, and source-to-target reconciliation.

  • Orchestration: Parameterized pipelines, dependencies, scheduling, logging, alerts, retries, and safe reruns without duplicating data.

  • Security and governance: Workspace and item permissions, data-level access controls, secure connections, sensitivity labels, and lineage.

  • Deployment: Git integration, deployment pipelines, and controlled promotion across development, test, and production.

  • Performance and operations: Spark/SQL tuning, Delta table optimization, production troubleshooting, and capacity consumption analysis using Fabric Capacity Metrics.

  • Analytics integration: Curated datasets for Power BI and an understanding of semantic models, Direct Lake, and refresh dependencies.

Business and delivery requirements

  • Proven experience across at least two business domains, preferably three, such as Procurement, HR, Finance, Sales, or Inventory, supported by real delivered projects.

  • Ability to explain each domain’s business processes, key KPIs, source data, reporting requirements, and their personal contribution to implementation.

  • Translate business requirements into documented data mappings, transformation rules, and acceptance criteria.

  • Understand data grain, business keys, historical reporting, and reconciliation requirements.

  • Communicate clearly with business stakeholders, architects, analysts, and source-system teams.

  • Own estimates, delivery commitments, testing, UAT support, documentation, and operational handover.

  • Explain technical decisions in terms of business value, cost, performance, and reliability.

Preferred qualifications

  • Microsoft Certified: Fabric Analytics Engineer Associate (DP-600).

  • Experience integrating Dynamics 365/Dataverse, SAP ECC, S4HANA , or other ERP/CRM platforms.

  • KQL, Eventstreams, Eventhouse, and real-time processing experience.

  • Azure Data Factory, Azure Databricks, ADLS Gen2, and Microsoft Purview experience.

  • Client-facing consulting experience.

Skills

ADLS Gen2Azure DatabricksAzure Data FactoryBronze/Silver/Gold ArchitectureChange-data CaptureDataflows Gen2Data-level Access ControlsDeduplicationDelta Table OptimizationDelta TablesDeployment PipelinesDimensional ModelingDirect LakeDynamics 365/DataverseERP/CRM IntegrationEventhouseEventstreamsFabric Capacity MetricsFabric Data FactoryFact/dimension TablesFull And Incremental LoadsGit IntegrationKQLLakehouseLineageMicrosoft FabricMicrosoft PurviewNotebooksOneLakeParameterized PipelinesPower BIPython/PySparkReal-time ProcessingS4HANASAP ECCSemantic ModelsSensitivity LabelsSlowly Changing DimensionsSource-to-target ReconciliationSpark/SQL TuningSQL/T-SQLUpsertsValidation RulesWarehouseWorkspace And Item Permissions

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