Senior Data Platform Engineer - Microsoft Fabric

Summary

The Senior Data Platform Engineer is a hands-on technical role responsible for building, maintaining, and continuously improving SJVCi’s Microsoft Fabric data platform. This position develops scalable data pipelines and trusted data solutions while supporting data quality, security, monitoring, deployment, and reliability across San Joaquin Valley College, Carrington College, and Shared Services.

Compensation: The starting pay range for this position is $105,000 - $125,000 annually.

Key Responsibilities

• Design, build, and enhance scalable data solutions using Microsoft Fabric, OneLake, Lakehouses, Warehouses, SQL, Python/PySpark, Spark, and Delta Lake.

• Develop reliable Bronze, Silver, and Gold data assets, pipelines, transformations, and analytics-ready data models.

• Build reusable, governed data products that support executive, operational, and analytical reporting across the organization.

• Establish automated testing, deployment, monitoring, data-quality, and recovery processes for production data workloads.

• Optimize platform performance, capacity utilization, query performance, storage, and refresh processes.

• Implement secure, least-privilege access and support data lineage, governance, and compliance requirements.

• Modernize legacy data processes and replace one-off solutions with scalable, reusable engineering patterns.

• Partner with data owners, analysts, BI developers, technical teams, and business stakeholders to deliver trusted data solutions.

• Provide technical leadership through architecture guidance, code reviews, reusable standards, documentation, and mentoring.

• Troubleshoot production issues and drive root-cause resolution and continuous improvement.

NOTE: Employee may occasionally be required to perform job-related tasks other than those specifically stated in this description. The duties and responsibilities are carried out in a manner that is consistent with the mission, values and operating principles of San Joaquin Valley College, Inc.

Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Software Engineering, or a related field, or an equivalent combination of education and directly relevant experience.

• 7+ years of progressive experience in data engineering, data warehousing, analytics engineering, database development, or data platform engineering.

• Hands-on production experience with Microsoft Fabric or a comparable modern lakehouse platform.

• Advanced SQL skills, including query optimization, schema design, dimensional modeling, and performance tuning.

• Strong Python and/or PySpark skills with experience using Spark-based processing and Delta Lake concepts.

• Experience designing layered Bronze/Silver/Gold data architectures and reusable data products.

• Experience with Git, code reviews, automated testing, CI/CD, and controlled production releases.

• Experience with production monitoring, data-quality validation, troubleshooting, runbooks, and recovery processes.

• Working knowledge of Power BI semantic models, star schemas, measures, and refresh processes.

• Understanding of role-based access, secure service identities, credentials, data classification, and least-privilege security.

• Ability to translate business requirements into scalable technical solutions and communicate effectively with technical and business stakeholders.

Reporting & Team Structure

This position has no supervisory responsibilities.

Physical Demands

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Work Environment

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.