Data Engineer

Lead Data Engineer

Location: Encino CA /LA California /Atlanta GA

Role Overview:

We are seeking a Lead Data Engineer with expertise in data modeling , Data Vault architecture , and cloud data warehouse (CDW) architecture utilizing the Kimball model . The ideal candidate will have hands-on experience with data fabric technologies (e.g., Databricks), Spark , and Python on Azure Cloud . This role involves designing, implementing, and optimizing data pipelines and data platforms to support business intelligence and advanced analytics.

Key Responsibilities:

• Design and implement scalable and efficient data models, including Data Vault and Kimball dimensional modeling for cloud-based data warehouses.
• Architect and manage Azure Cloud -based data infrastructure, ensuring scalability, security, and performance.
• Develop and optimize data pipelines using Databricks , Spark , and other data fabric tools to process large volumes of data.
• Collaborate with data scientists, analysts, and business stakeholders to understand data needs and deliver high-quality solutions.
• Implement best practices for data engineering, including data quality, governance, and lifecycle management.
• Build and maintain infrastructure-as-code using Terraform or other DevOps tools.
• Create reusable data engineering components for ingestion, transformation, and orchestration.
• Troubleshoot, optimize, and maintain existing data systems to meet evolving business needs.

Required Skills and Experience:

• 10+ years of experience in Data Engineering or a similar role, with a proven track record of leading data projects.
• Expertise in Data Vault 2.0 architecture and Kimball modeling for data warehouse design.
• Proficiency with Azure Data Services (e.g., Azure Data Factory, Azure Synapse, Azure Databricks).
• Hands-on experience with Databricks and Spark for distributed data processing.
• Strong programming skills in Python for ETL/ELT development and automation.
• Deep understanding of CDW architecture and data fabric frameworks .
• Experience with CI/CD pipelines and infrastructure-as-code tools like Terraform .
• Solid knowledge of data governance, security, and compliance best practices.

Educational Qualifications:

• Bachelor’s degree in Computer Science, Data Engineering, or related fields. Master’s degree preferred.
• Certifications in Data Engineering , Azure Cloud , or Databricks are highly desirable.