Sr. Azure Databricks Architect

Sr. Azure Databricks Architect

Location: Kennesaw, GA

Duration: Fulltime

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 Modeling & 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.