Sr. Azure Databricks Architect

Role : Sr. Azure Databricks Architect

Location: Kennesaw GA

Job Description

Must Have Technical/Functional Skills

• Experience: 10 years in data engineering or architecture, with at least 4 years in a senior or architect role focused on cloud solutions using Databricks
• Azure Expertise: Deep, hands-on experience with the Azure data ecosystem, including Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), and Azure Synapse Analytics.
• Databricks Proficiency: Proven expert-level ability to design and build solutions using Databricks for large-scale data processing (ETL/ELT) and analytics.
• Modern Data Tooling: Strong, practical experience using dbt for data transformation, modeling, and testing within a cloud data warehouse environment.
• Data Warehousing: Solid understanding of data warehousing principles, including Kimball/Inmon methodologies, dimensional modeling, and schema design.
• Infrastructure as Code (IaC): Experience using tools like Terraform or ARM templates to define and manage cloud infrastructure.

Roles & Responsibilities

• Architect & Design: Design and implement end-to-end modern data architecture on the Azure cloud platform, including data lakes, data warehouses, and analytics solutions.
• Lead Technical Implementation: Spearhead the development of data pipelines and modeling layers using Azure services (Azure Data Factory, Synapse Analytics, ADLS Gen2), Databricks, and dbt.
• Data Modelling & Warehousing: Develop and maintain robust, scalable data models that support business intelligence and analytics needs. Define and enforce data modeling standards and best practices.
• Strategy & Governance: Drive the strategy for our cloud data platform, ensuring security, governance, and cost-effectiveness are embedded into the architecture from day one.
• Migration Leadership: Plan and execute the migration of on-premise data warehouses and databases to the Azure cloud, minimizing downtime and ensuring data integrity.
• Collaboration & Mentorship: Work closely with data engineers, analysts, and business stakeholders to understand requirements and deliver effective solutions. Mentor junior members of the team on best practices in cloud data architecture.