Azure Fabric Data Engineer

Q1 Technologies, Inc.; Newark (NJ); On-site; USD 85,000 - 110,000; Full time

Job summary

A leading technology solutions provider is seeking a Fabric Data Engineer Associate Certified to lead the design and implementation of scalable data solutions using Microsoft Azure Data services. In this role, you will develop modern data ingestion and transformation pipelines while defining data governance and architecture standards. The ideal candidate will have strong expertise in Azure Data Factory, Azure Synapse, and a passion for technical leadership and optimizing data solutions. This position is based in Newark, New Jersey.

Qualifications

• Experience in designing and implementing secure data solutions.
• Proficiency in building modern ETL/ELT pipelines using Azure.
• Knowledge of data governance standards and quality management.

Responsibilities

• Lead the design and implementation of scalable data solutions.
• Develop data ingestion and transformation pipelines using Azure services.
• Provide technical leadership and mentorship for best practices.

Skills

Data governance

Cloud solutions

ETL/ELT processes

Azure infrastructure

Technical leadership

Performance tuning

Tools

Microsoft Azure Data services

Azure Data Factory

Azure Synapse

Azure Data Lake

Job description

Overview

• Fabric Data Engineer Associate Certified
• Lead the design and implementation of scalable, secure, and cost-effective data solutions using Microsoft Azure Data services (e.g., Azure Synapse, Azure Data Factory, Azure Data Lake).
• Develop modern data ingestion and transformation pipelines (ETL/ELT), leveraging Fabric (Data Factory, Synapse Engineering) components for high-volume data processing.
• Define data governance, security, and architecture standards, including data modeling, data quality, and metadata management across the Azure ecosystem.
• Provide technical leadership and mentorship, ensuring best practices for performance tuning and optimization of data storage and analytics solutions.
• Collaborate with business and engineering teams to translate complex data requirements into robust, future-proof architectural blueprints.
• Implement CI/CD practices for data pipelines and infrastructure as code (IaC) to automate deployment and ensure operational excellence.