Lead Data Platform Engineer - Lakehouse & Fabric

Halozyme, Inc.; San Diego (CA); On-site; USD 175,000 - 185,000; Full time

Benefits offered by this job

Employee Stock Purchase Program

401(k) matching

Tuition reimbursement

Job summary

You’ll guide a team, contribute code, and define standards for ingestion, metadata, and CI/CD, ensuring fast, secure access to trusted data for analytics.

Qualifications

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related technical field; 10+ years in data engineering or analytics.
• Master’s degree preferred
• Equivalent combination of experience and education may be considered
• Deep, hands-on expertise with Microsoft Fabric (lakehouses, notebooks, Data Factory, deployment pipelines)

Responsibilities

• Serve as the technical lead for Halozyme’s Microsoft Fabric-based data lakehouse — workspace topology, OneLake storage design, medallion-layer standards (bronze/silver/gold), Spark and SQL compute configuration, and CI/CD pipeline design
• Provide technical leadership and mentorship to data and analytics engineers through code reviews, architectural guidance, and hands-on problem solving
• Design and build production-grade data ingestion pipelines across 50+ source systems using Data Factory, dataflows, shortcuts, and mirroring patterns
• Partner with business stakeholders to understand data requirements, prioritize platform capabilities, and ensure the UDP delivers actionable value
• Define and enforce platform engineering standards: naming conventions, branching strategies, testing patterns, runbooks
• Build and maintain the semantic layer (Power BI datasets, gold-layer views) for trusted data products

Skills

PySpark

T-SQL

Python

Leadership

Education

Bachelor's degree in Computer Science or related field

Master's degree preferred

Tools

Microsoft Fabric

Data Factory

Azure Synapse

GitHub Actions

Job description

You’ll guide a team, contribute code, and define standards for ingestion, metadata, and CI/CD, ensuring fast, secure access to trusted data for analytics.