Microsoft Fabric Data Engineering & Analytics Manager

Manager to lead the architecture, implementation, migration, and ongoing evolution of our enterprise data and analytics platform using Microsoft Fabric. The role will be responsible for establishing a scalable Fabric environment that consolidates data from multiple ERP, Finance, Sales, Marketing, and operational systems into a governed enterprise data platform supporting analytics, reporting, and downstream application integrations. The successful candidate must be capable of operating as both a senior technical architect and hands-on engineering leader, with deep experience designing enterprise data platforms, building ingestion and transformation pipelines, implementing Lakehouse and Data Warehouse architectures, and enabling Power BI and downstream integrations., Lead the end-to-end architecture and implementation of the organization’s Microsoft Fabric enterprise data platform. Design the target architecture across OneLake, Fabric Lakehouse, Fabric Warehouse, Data Factory/Data Pipelines, Dataflows Gen2, notebooks, Spark and Power BI. Establish enterprise standards for Fabric workspaces, domains, capacities, environments, security, deployment, monitoring and governance. Design and implement ingestion pipelines from multiple business systems, including ERP, Finance, CRM, e-commerce, marketing, operational and third-party platforms. Develop scalable ingestion patterns for business-unit and source-specific pipelines, including batch and, where appropriate, near-real-time ingestion. Design and implement a medallion/layered architecture covering raw/staging, cleansed/conformed/Silver and business-ready/Gold data. Architect and build enterprise Lakehouse and Data Warehouse solutions using Microsoft Fabric. Define data models, schemas, dimensional models, fact/dimension structures, aggregation strategies and reusable enterprise data products. Lead data cleansing, standardization, conformity and business-unit grouping across disparate source systems. Establish common definitions and transformation rules to produce trusted, business-ready KPIs and analytics datasets. Design solutions for enterprise data integration across systems such as Oracle EBS, Microsoft Dynamics, Workday Adaptive, CRM applications, e-commerce platforms, operational systems and Microsoft 365 sources. Build reusable integration frameworks supporting both analytics consumers and downstream operational applications. Implement robust status tracking, logging, exception handling, retry mechanisms, alerting, reconciliation and data-quality monitoring across pipelines. Establish data validation and reconciliation processes from source through presentation layer. Optimize Fabric workloads for performance, scalability and cost, including capacity planning, workload management, partitioning, file optimization and query performance. Design security using appropriate RBAC, workspace permissions, least-privilege access, row/column/object-level security and data protection controls. Establish governance practices covering data ownership, lineage, metadata, data quality, retention, classification and auditability. Work with business stakeholders to translate Finance, Commercial, Supply Chain and Business Technology requirements into scalable data products. Partner closely with Power BI developers and analytics teams to establish optimized semantic models and reporting datasets. Define Dev/Test/Prod environments, CI/CD, source control, release management and deployment pipelines for Fabric artifacts. Establish engineering standards, naming conventions, reusable frameworks, documentation and development best practices. Mentor data engineers and provide technical leadership, architecture reviews and code/design reviews. Develop the Fabric implementation roadmap and support migration from existing Azure Data Lake, legacy reporting/data extraction solutions and point-to-point integrations. Evaluate existing integrations and determine appropriate migration, coexistence or retirement strategies. Maintain technical architecture, data-flow diagrams, source-to-target mappings, transformation specifications and operational runbooks.

The ideal candidate should have 10+ years of enterprise data engineering/data warehousing experience, including significant architecture or technical leadership responsibility, and strong recent hands-on Microsoft Fabric experience. Deep expertise should include Microsoft Fabric, OneLake, Lakehouse, Fabric Warehouse, Data Factory/Pipelines, Dataflows Gen2, notebooks, Spark/PySpark, SQL, T-SQL, Delta/Parquet, dimensional modelling, ETL/ELT, medallion architecture, semantic modelling, Power BI integration, Azure data services, Git/source control, CI/CD, APIs and enterprise integration patterns. Experience integrating complex ERP environments particularly Oracle EBS and Microsoft Dynamics would be highly desirable. The individual should also understand Fabric capacity management, performance optimization, monitoring, security, governance, disaster recovery/business continuity considerations, data lineage and enterprise data-quality practices. Leadership Expectations This is not intended to be a purely managerial position. The individual must be comfortable designing the architecture, building or troubleshooting pipelines, reviewing SQL/PySpark, solving performance problems and working directly within Fabric, while simultaneously leading the broader implementation and engineering team.