Microsoft Fabric Engineer | Camden Corporate Office

Job Summary

The Microsoft Fabric Engineer is responsible for designing, building, and operating Camden's modern data platform on Microsoft Fabric. As part of IT, this role owns the end-to-end data engineering lifecycle — ingestion, transformation, architecture, platform engineering, CI/CD, backup and disaster recovery, data modeling, semantic layer delivery, and downstream enablement for Power BI, AI workloads, and operational applications. The Fabric Engineer partners closely with the BI team, the Application Development, and AI teams to establish the Fabric environment, standards, and shared data foundations that enable those teams to deliver reporting, operational use cases, AI-ready data products, and production integrations.

Essential Functions

Platform Engineering

• Design and implement Fabric workspaces, lakehouses, warehouses, and OneLake structures aligned to Camden's data domains.
• Define and govern Fabric environment architecture, including workspace strategy, dev/test/prod separation, naming standards, access patterns, and capacity assignment.
• Build and operate data pipelines using Fabric Data Factory, Dataflows Gen2, and Spark notebooks.
• Implement medallion architecture (bronze / silver / gold) with clear ownership and contracts between layers, with IT accountable for bronze, shared responsibility between IT and BI for silver, and BI accountable for gold.
• Own administration and tuning of Camden’s F64 Fabric capacity, including workload management, performance tuning, monitoring and throttling analysis, cost optimization, and workload isolation across Fabric capacities.
• This job description is not an all-inclusive list of duties and responsibilities. Camden may add or change responsibilities in order to meet business and organizational needs.

Data Modeling & Semantic Layer

• Establish and enforce naming conventions, documentation, and lineage practices.
• Partner closely with the BI team on the shared silver layer and BI-owned gold-layer needs by providing trusted data models, semantic design standards, certified datasets, and a well-governed Fabric environment that enables enterprise analytics.

Integration & Delivery

• Ingest data from Camden's core systems — property management (RealPage), ERP, CRM, marketing, HR, and operational telemetry.
• Expose Fabric data to Power BI, AI/ML workloads, Copilot Studio, and downstream applications.
• Partner closely with the Application Development and AI teams to define solution patterns, data contracts, and shared integration approaches that enable those teams to build operational use cases and AI solutions within the Fabric environment.

Governance, Security & Reliability

• Implement Purview integration, sensitivity labels, row/column-level security, and data quality monitoring.
• Establish and govern Camden’s engineering standards for Fabric architecture, deployment, operations, resilience, and platform performance.
• Define, implement, and continuously improve Camden’s CI/CD standards for Fabric artifacts, including Git integration, branching strategy, deployment pipelines, environment promotion, and release governance across development, test, and production.
• Define and operationalize Camden’s backup, business continuity, and disaster recovery strategy for Fabric, including recovery objectives, cross-region considerations, protection of OneLake data and workspace artifacts, restore procedures, and regular failover testing.
• Own monitoring, alerting, and incident response for the data platform.
• Create and maintain operational runbooks, support procedures, and escalation paths for Fabric platform administration, incidents, maintenance windows, and recovery events.

Requirements

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or related field; equivalent experience considered.
• 5+ years of data engineering experience, including 1+ year hands-on with Microsoft Fabric (or strong recent Azure Synapse / Databricks experience with a clear path to Fabric).
• Strong SQL and Python (PySpark) skills; experience with Delta Lake / Parquet.
• Proven experience designing dimensional and semantic models for analytics (star schema, slo