Microsoft Fabric Engineer | Camden Corporate Office at Camden

Houston, Texas, United States -

Full Time

Start Date

Immediate

Expiry Date

19 Sep, 26

Salary

0.0

Posted On

21 Jun, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Microsoft Fabric, PySpark, SQL, Data Modeling, CI/CD, Azure DevOps, Power BI, Delta Lake, Data Factory, Azure Synapse, Databricks, Purview, API Integration, Dimensional Modeling, Capacity Tuning, Disaster Recovery

Industry

Real Estate

Description

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, slowly changing dimensions, etc.). * Strong understanding of Power BI semantic models, tabular modeling, and enterprise reporting patterns. * Experience with Git-based development, Azure DevOps, and deployment pipelines for analytics or data platforms. * Experience defining and operationalizing CI/CD practices for data platforms, including branching strategy, release governance, environment promotion, and deployment automation for Microsoft Fabric, Power BI, Azure, or similar analytics platforms. * Experience managing and tuning shared analytics capacities, including Microsoft Fabric and/or Power BI Premium/Fabric F SKUs, with a focus on utilization monitoring, throttling analysis, workload balancing, and cost-effective performance optimization. * Experience integrating SaaS solutions with enterprise data platforms and applications using APIs, connectors, and event-driven patterns. * Working knowledge of database administration for SQL Server environments, including backup and recovery, job scheduling, index and query performance tuning, security, and routine operational support. * Ability to provide backup support for production SQL Server operations in coordination with application teams and the primary DBA. * Experience defining backup, business continuity, and disaster recovery strategies for cloud data platforms, including recovery point and recovery time objectives, regional failover planning, restoration procedures, and validation through documented runbooks and testing. * Preferred certifications include Microsoft DP-600 (Fabric Analytics Engineer), DP-700 (Fabric Data Engineer), or PL-300. * Preferred experience with real estate, property management, or REIT data domains. * Preferred experience integrating Fabric with AI workloads, including Azure OpenAI, Copilot, vector search, and embedding pipelines. * Preferred background in data governance frameworks, such as Purview, data catalogs, and master data management. And here’s the fine print HR wants you to know: * Job is intermittently sedentary but requires mobility (i.e., climb stairs) * Will use some repetitive motion of hand-wrist in using computer and writing * Works in a typical office setting * Emotional stability and personal maturity are important attributes in this position * Must handle stressful, urgent, novel and diverse work situations on a daily basis * May require long hours and odd schedules (including weekends) * Position requires periodic travel by automobile to handle work-related activities * May require airline travel, out-of-town and /or overnight trips * Attendance and punctuality is essential for success in this position * Hazards can be minimized with proper lifting techniques, SDS, general safety training, and wearing appropriate PPE * Contact your HR team for the position’s Physical Demands Analysis 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. Employees must meet qualification standards that are job-related and consistent with business necessity and must be able to perform the essential functions of the position, with or without reasonable accommodations. To learn more about our awesome Benefits, visit Camden Benefits [https://www.camdenliving.com/benefits].

Responsibilities

Design, build, and operate a modern data platform on Microsoft Fabric, managing the end-to-end data engineering lifecycle from ingestion to semantic layer delivery. Partner with BI and AI teams to establish environment standards, governance, and shared data foundations for enterprise analytics.