Senior Microsoft Fabric Data Engineering & Analytics Manager

Senior Microsoft Fabric Data Engineering & Analytics Manager
Role Summary
We are seeking a highly experienced Senior Microsoft Fabric Data Engineering & Analytics
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.
Key Responsibilities
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.
Required Technical Experience
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.