Manager, Data Platform Engineer - Microsoft Fabric

About the role

CHANEL is looking for a Manager, Data Platform Engineer – Microsoft Fabric to join our Enterprise Data Management (EDM) team in New York City. You will build trusted data products and production-ready pipelines on Microsoft Fabric/FDP, from source ingestion through curated and governed layers that can be consumed confidently by BI, analytics, and other approved use cases. This role works closely with the Enterprise Data Platform & Integration Architect, BI & Analytics, Data Governance, application and source-system teams, and delivery partners. The ideal candidate brings up to 5 years of hands-on data engineering or data platform engineering experience, including production delivery on modern cloud data platforms, direct Microsoft Fabric implementation experience, and a passion for engineering reliable, observable, and well-documented data solutions.

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, routing remediation to the accountable team while supporting 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