Azure Data Architect: Cloud Analytics & Migrations Lead

Navisoft; Atlanta, Northern (GA, KY); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Navisoft is seeking an Azure Data Architect to design and implement modern data architecture on Azure, including data lakes, data warehouses, and analytics solutions. You will lead technical implementation of data pipelines and modeling layers using Azure services, Databricks, and dbt, with a focus on cloud data warehouse migrations.

The role requires extensive Azure expertise and leadership experience in cloud data platforms, emphasizing security, governance, and cost-effectiveness across

Qualifications

• 10+ years in data engineering/architecture, with 4+ years as a senior/architect focused on cloud solutions.
• Deep experience with Azure Data Factory (ADF), ADLS, and Azure Synapse Analytics.
• Expert-level ability with Databricks for large-scale data processing and analytics.
• Strong experience using dbt for data transformation and modeling.
• Solid understanding of data warehousing principles.
• Experience using IaC tools like Terraform or ARM templates.

Responsibilities

• Design and implement end-to-end modern data architecture on Azure.
• Lead development of data pipelines and modeling layers using Azure services, Databricks, and dbt.
• Develop and maintain scalable data models.
• Drive strategy for cloud data platform, ensuring security, governance, and cost-effectiveness.
• Plan and execute migration of on-premise data warehouses to Azure.
• Collaborate with data engineers, analysts, and stakeholders.
• Mentor junior team members.

Job description

Navisoft is seeking an Azure Data Architect to design and implement modern data architecture on Azure, including data lakes, data warehouses, and analytics solutions. You will lead technical implementation of data pipelines and modeling layers using Azure services, Databricks, and dbt, with a focus on cloud data warehouse migrations.

The role requires extensive Azure expertise and leadership experience in cloud data platforms, emphasizing security, governance, and cost-effectiveness across