Senior Data Engineer & Microsoft Fabric AI Director

DataJobs; Ewing Township (NJ); On-site; USD 140,000 - 160,000; Full time

Job summary

GS1 Global Office is seeking a senior Data Engineer Director (individual contributor) to design, build, and support secure, scalable enterprise data and analytics solutions. The role centers on Microsoft Fabric, Azure data services, and Power BI, including AI-enabled data pipelines to Claude AI.

The onsite role in Ewing, NJ involves delivering production data engineering across lakehouse and warehouse architectures, building RAG pipelines, and leading data architecture decisions with governance

Qualifications

• Bachelor’s degree in computer science, data engineering, information systems, or a related field, or equivalent professional experience.
• At least five years of experience in data engineering, BI, or analytics with production solutions.
• Strong experience with Microsoft Fabric or Azure Synapse/Databricks.
• Power BI reports, semantic models, and datasets.

Responsibilities

• Design, develop, and maintain scalable data pipelines using Microsoft Fabric and Azure data services.
• Build Lakehouse and Data Warehouse solutions with semantic models.
• Develop RAG pipelines and AI-enabled data retrieval for Claude AI and other LLMs.
• Develop Power BI dashboards, reports, datasets, and semantic models for insights.
• Ensure data security, governance, and cost efficiency across pipelines.

Skills

Data engineering

SQL

Python

PySpark

Education

Bachelor's degree in computer science / data-related field

Tools

Power BI

Azure Data Factory

Microsoft Fabric

Azure Synapse

Databricks

Git

Job description

GS1 Global Office is seeking a senior Data Engineer Director (individual contributor) to design, build, and support secure, scalable enterprise data and analytics solutions. The role centers on Microsoft Fabric, Azure data services, and Power BI, including AI-enabled data pipelines to Claude AI.

The onsite role in Ewing, NJ involves delivering production data engineering across lakehouse and warehouse architectures, building RAG pipelines, and leading data architecture decisions with governance