Senior Technical Lead – Data Engineering / DevOps

Role Overview

We are looking for an experienced Senior Technical Lead with strong expertise in Microsoft Azure, Microsoft Fabric, Data Engineering, and DevOps.

This role requires a professional with approximately 60% DevOps expertise and 40% Data Engineering experience, capable of building reliable data pipelines, managing CI/CD deployments, and supporting enterprise-scale Microsoft Fabric solutions.

Key Responsibilities

• Design, build, and maintain reliable data pipelines and scheduled data processing jobs using Microsoft Fabric.
• Work with Fabric Data Factory, Lakehouse, and Warehouse for data ingestion, transformation, and orchestration.
• Develop and maintain CI/CD pipelines for Microsoft Fabric solutions using Git and Azure DevOps.
• Implement YAML-based pipeline configurations and deployment automation.
• Support Azure Data Factory to Microsoft Fabric migration and integration initiatives.
• Manage secure configurations, credentials, identities, and deployment processes.
• Implement Identity and Access Management and secure connectivity across environments.
• Work with Azure networking components, including VNets, DNS, private endpoints, and network security.
• Troubleshoot and resolve data pipeline, infrastructure, and deployment issues.
• Ensure reliability and operational stability of production data workloads.

Mandatory Technical Skills

• Strong hands-on experience with Microsoft Fabric.
• Azure Data Factory (ADF).
• Azure DevOps and Git.
• YAML pipelines and CI/CD automation.
• Data Lakehouse architecture.
• Identity and Access Management (IAM).
• Azure infrastructure and networking.
• Production data pipeline support and troubleshooting.

Preferred Qualifications

• Experience migrating data workloads from Azure Data Factory to Microsoft Fabric.
• Knowledge of Microsoft Fabric deployment and automation APIs.
• Experience with enterprise data engineering and DevOps implementation.
• Strong problem-solving and communication skills.

Important Requirement

The ideal candidate should have a strong DevOps background (60%) combined with Data Engineering expertise (40%).

Candidates must be located in the PST time zone.