Data Architect

About the Role

On behalf of our client, we are looking for an experienced Data Architect to lead the design, implementation, and governance of their enterprise data and analytics platform, built on Microsoft Fabric with a strong Databricks background. You will be the technical authority on modern lakehouse architecture spanning data engineering, data warehousing, real-time analytics, and Power BI translating business requirements into scalable, secure, and cost-efficient solutions across the Fabric/Databricks ecosystem.

This is a high-impact role for someone who wants to shape a modern data platform from the ground up, bringing deep lakehouse and Spark expertise to a Fabric-first environment, and mentor teams as they adopt it.

What You'll Do

* Design and own the end-to-end architecture for Microsoft Fabric, including OneLake, Lakehouse, Data Warehouse, Data Factory pipelines, Real-Time Intelligence, and Power BI semantic models.
* Define data platform standards: medallion architecture (bronze/silver/gold), naming conventions, workspace structure, capacity planning, and CI/CD practices.
* Lead migrations from legacy platforms (e.g., Synapse, Azure Data Factory, SSAS, on-prem SQL Server) into Fabric.
* Architect security and governance frameworks - including workspace roles, OneLake data access policies, row-level security, sensitivity labels, and integration with Microsoft Purview.
* Optimize Fabric capacity usage (F-SKUs), monitor performance, and manage cost governance across workspaces.
* Collaborate with data engineers, analysts, and business stakeholders to design scalable data models and pipelines.
* Establish DevOps practices for Fabric (Git integration, deployment pipelines, environment promotion).
* Provide technical leadership, code/design reviews, and mentorship to data engineering and BI teams.
* Stay current with Fabric's evolving feature set and advise on adoption roadmaps.
* Evaluate and architect interoperability between Databricks and Fabric where relevant (e.g., shortcuts to OneLake, Delta Lake compatibility, Unity Catalog vs. Fabric governance models).
* Advise on platform strategy where Databricks workloads (Spark jobs, MLflow, Delta Live Tables) need to coexist with or migrate into a Fabric-centric environment.
* Bring lakehouse design best practices (Delta Lake, Unity Catalog, cluster/job optimization) to inform Fabric architecture decisions.

What We're Looking For

Required:

* 5+ years of experience in data architecture, data engineering, or BI, with hands-on experience across Microsoft Fabric (or Azure Synapse) and Databricks.
* Strong background working within Databricks cluster architecture, Delta Lake, Unity Catalog, Delta Live Tables, MLflow, and job/workflow orchestration.
* Strong knowledge of OneLake, Lakehouse/Warehouse architecture, Dataflows Gen2, Data Pipelines, and Notebooks (PySpark/Spark SQL).
* Deep experience with Power BI, including semantic (Direct Lake) models, DAX, and report/dataset governance.
* Solid understanding of data modeling (dimensional modeling, medallion architecture) across both lakehouse platforms.
* Experience with T-SQL, Python, and PySpark/Spark SQL.
* Familiarity with Azure services: Azure Data Lake Storage, Azure Active Directory (Entra ID), Azure DevOps/GitHub.
* Experience designing for data security, compliance, and governance at enterprise scale (across Unity Catalog and/or Microsoft Purview).
* Strong communication skills able to work with both technical teams and business stakeholders.

Nice to Have:

* Microsoft certifications (e.g., DP-600, DP-700, or Azure Solutions Architect).
* Databricks certifications (e.g., Databricks Certified Data Engineer Professional, Databricks Certified Solutions Architect).
* Experience with Microsoft Purview for data governance and cataloging.
* Background in real-time analytics (Eventstreams, KQL databases, or Databricks Structured Streaming).
* Prior experience leading platform migrations either Databricks-to-Fabric, Fabric-to-Databricks, or hybrid coexistence architectures.