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Chanel

Designs, sells luxury fashion and cosmetics

Manager Data Platform Engineer - Microsoft Fabric

Data EngineeringConfirmed live in the last 24 hours
Full-timeNew York, NY, USA$70k - $160k

About the Job

Requirements

  • Demonstrated hands-on Microsoft Fabric implementation experience across several of the following: OneLake, Lakehouse, Warehouse, Fabric Data Factory/Data Pipelines, notebooks, PySpark, SQL, Delta Lake, Dataflows Gen2, shortcuts, mirroring, Git integration, and deployment pipelines.
  • Experience designing medallion layers and source-to-curated data flows, including incremental ingestion, transformation, schema evolution, history management, restartability, idempotency, dependency management, performance tuning, controlled reprocessing, and recovery handling.
  • Strong experience with automated unit, integration, regression, reconciliation, and deployment testing, together with data-quality controls, operational logging, monitoring, alerting, failure classification, recovery procedures, and runbooks.
  • Experience with Git-based source control, code review, CI/CD, deployment pipelines, environment configuration and promotion, secure access, release evidence, rollback planning, and disciplined release management.
  • Working knowledge of Purview, lineage, metadata, security, privacy, and governance controls as they apply to engineered data solutions.
  • Ability to create clear technical documentation, mappings, runbooks, support procedures, and handoff evidence that other engineers can operate.
  • A bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience.
  • Strong collaboration and communication skills across technical and non-technical stakeholders.

Responsibilities

  • Design, build, test, deploy, and support Microsoft Fabric/FDP data products and pipelines across ingestion, transformation, lakehouse, warehouse, and curated data layers.
  • Engineer scalable Fabric data products using appropriate combinations of OneLake, Lakehouse, Warehouse, Fabric Data Factory/Data Pipelines, notebooks, PySpark, SQL, Delta Lake, Dataflows Gen2, shortcuts, mirroring, and medallion architecture.
  • Build restartable and idempotent ingestion and transformation pipelines with schema-evolution handling, dependency management, controlled reprocessing, and robust exception handling.
  • Embed automated testing, reconciliation, data-quality controls, lineage, monitoring, alerting, failure evidence, and controlled exception routing into each data product.
  • Diagnose and classify failures across source data, integration, Fabric processing, orchestration, and downstream consumption layers, route remediation to the accountable team, and support Fabric engineering quality and reliable platform delivery.
  • Apply disciplined DataOps and software-engineering practices across source control, code review, automated testing, CI/CD, deployment pipelines, environment configuration and promotion, access controls, rollback planning, release evidence, and separation of duties.
  • Use platform monitoring and performance information to help improve reliability, capacity utilization, and cost efficiency.
  • Maintain accurate source-to-target mappings, transformation logic, data-quality rules, technical lineage, ownership metadata, security requirements, change history, runbooks, known limitations, and support handoff materials throughout the data-product lifecycle.
  • Contribute to reviews of partner-delivered code, testing, controls, documentation, and production-readiness evidence.
  • Deliver tested and trusted curated data products for BI & Analytics and other approved consumers, collaborating on availability, lineage, performance, interfaces, and change impacts while BI & Analytics retains semantic-model, metric, reporting-standard, and Power BI architecture responsibilities.
  • Contribute reusable engineering patterns and practical improvements that help EDM scale Fabric delivery without creating one-off pipelines or unsupported solutions.

About the Company

Chanel

Designs, sells luxury fashion and cosmetics

1) What does Chanel do? Chanel is a luxury fashion house that offers a range of high-end products including fashion, accessories, fragrances, skincare, makeup, jewelry, and watches, targeting affluent customers worldwide. 2) How does its product work? It designs and sells premium, timeless items through owned boutiques, official online channels, and authorized retailers, supported by strong marketing, fashion shows, and brand storytelling to maintain desirability and loyalty. 3) How is Chanel different from competitors? It combines a storied brand heritage with exclusive, premium products and strict distribution control, creating a sense of rarity and prestige that appeals to luxury buyers. 4) What is Chanel's goal? To preserve its elite brand status while growing a loyal, affluent customer base by delivering consistently refined, timeless designs and a premium consumer experience.

Company size
10,001+
Company stage
Debt Financing
Total funding
$770M
Headquarters
Argueil, France
Founded
1883

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