Manager, Data Platform Engineer - Microsoft Fabric

Chanel • New York City, NY

6d • Onsite

About The Position

CHANEL is seeking a Manager, Data Platform Engineer to join its Enterprise Data Management team in New York City. The role builds trusted data products and production-ready pipelines on Microsoft Fabric/FDP, from source ingestion through curated and governed layers for BI, analytics, and other approved uses. It works closely with the Enterprise Data Platform & Integration Architect, BI & Analytics, Data Governance, application and source-system teams, and delivery partners. The position combines hands-on engineering with responsibility for reliable, observable, well-documented solutions and reusable delivery practices. New York City employees are required to work on site three days per week, and limited travel may be required to collaborate with U.S. and global teams. A bachelor's degree in a related field or equivalent practical experience is required. The anticipated base salary range is $70,000–$160,000; variable pay may also be offered.

Requirements

• 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, along 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.
• Strong collaboration and communication skills across technical and non-technical stakeholders.
• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience.
• Up to 5 years of hands-on data engineering or data platform engineering experience, including production delivery on modern cloud data platforms, as described in the role overview.

Responsibilities

• Design, build, test, deploy, and support Microsoft Fabric/FDP data products and pipelines across ingestion, transformation, lakehouse, warehouse, and curated 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 data products.
• Diagnose and classify failures across source data, integration, Fabric processing, orchestration, and downstream consumption, and route remediation to accountable teams.
• Apply DataOps and software-engineering practices for 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 improve reliability, capacity utilization, and cost efficiency.
• Maintain 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.
• Review 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 one-off pipelines or unsupported solutions.
• Collaborate with architects, analysts, governance partners, application teams, and external delivery teams, and share knowledge to establish repeatable practices.

Benefits

• Dedicated paid time off for wellbeing, including a two-week August office closure, and a wellbeing fund.
• Family and caregiving benefits, including parental leave, fertility support, MilkStork, and Care.com membership.
• Paid vacation, holidays, sick days, and volunteer days.
• 401(k) and other incentives.
• Medical, dental, vision, virtual care, One Medical, flexible spending accounts, health savings account, and employee assistance program.
• Life insurance, accidental death and dismemberment coverage, short-term disability, long-term disability, Health Advocate, international business travel accident and medical coverage, and commuter transit and parking benefits.
• Bonus potential and other variable pay may be offered.
• Career and leadership development programs, coaching, and online and live classes.
• Employee Resource Groups and opportunities to volunteer through CHANEL Community; CHANEL matches employee donations to select charitable organizations.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager