Senior Data Platform Engineer for Microsoft Fabric

Thomas James Homes

Aliso Viejo (CA)

On-site

USD 120,000 - 180,000

Full time

43 hours ago

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Job summary

Thomas James Homes seeks a senior data platform engineer to design, build, operate, and continuously improve the enterprise data platform in Microsoft Fabric, delivering lakehouses, warehouses, pipelines, and analytics that turn complex business data into trusted insights.

You will partner with business, application, and reporting teams to translate needs into scalable data solutions, enforce data governance, and enable self‑service reporting, AI, and operational decisions across the

Qualifications

Bachelor's degree in Computer Science, Data Engineering, or related field, or equivalent professional experience.
5+ years of experience in data engineering, analytics engineering, business intelligence, data analysis, or a related technology role.
Hands-on experience delivering production data pipelines, data models, warehouses or lakehouses, and analytics solutions in a Microsoft cloud environment.
Homebuilding, construction, real estate, finance, or operational analytics experience preferred

Responsibilities

Architect, build, test, deploy, and support end-to-end data solutions in Microsoft Fabric, including lakehouses, warehouses, pipelines, notebooks, dataflows, and semantic models.
Design and maintain scalable batch and near-real-time ingestion patterns from ERP, CRM, SaaS, APIs, files, databases, and other sources.
Develop transformation and data preparation logic using SQL, Python, PySpark, Notebooks, Dataflows Gen2, and Fabric data pipelines.
Implement dimensional, star-schema, and medallion-style data models for analytics-ready data products.
Build and optimize Power BI semantic models, measures, KPIs, and row-level security.
Partner with business stakeholders to define reporting requirements and translate findings into insights.
Establish automated data-quality controls, reconciliation checks, exception handling, alerting, and validation processes.
Monitor pipeline execution, capacity usage, query performance, refresh reliability, and platform health.
Create and maintain source-to-target mappings, data dictionaries, lineage documentation, and runbooks.
Lead design reviews and evaluate new Fabric capabilities.
Mentor data analysts, engineers, and power users on data modeling, SQL, Power BI, and Fabric development