Azure Data bricks Architect

Role & responsibilities

Job Summary:

We are seeking a highly experienced Azure Databricks Architect to design and implement large-scale data solutions on Azure. The ideal candidate will have a strong background in data architecture, data engineering, and data analytics, with a focus on Databricks.

Key Responsibilities:

• Design and implement end-to-end data solutions on Azure, leveraging Databricks, Azure Data Factory, Azure Storage, and other Azure services
• Lead data architecture initiatives, ensuring alignment with business objectives and best practices
• Collaborate with stakeholders to define data strategies, architectures, and roadmaps
• Develop and maintain data pipelines, ensuring seamless data integration and processing
• Optimize performance, scalability, and cost efficiency for Databricks clusters and data pipelines
• Ensure data security, governance, and compliance across Azure data services
• Provide technical leadership and mentorship to junior team members
• Stay up-to-date with industry trends and emerging technologies, applying knowledge to improve data solutions

Requirements:

• 15+ years of experience in data architecture, data engineering, or related field
• 6+ years of experience with Databricks, including Spark, Delta Lake, and other Databricks features
• Databricks certification (e.g., Databricks Certified Data Engineer or Databricks Certified Architect)
• Strong understanding of data architecture principles, data governance, and data security
• Experience with Azure services, including Azure Data Factory, Azure Storage, Azure Synapse Analytics
• Programming skills in languages such as Python, Scala, or R
• Excellent communication and collaboration skills

Nice to Have:

• Experience with data migration from on-premises data warehouses (e.g., Oracle, Teradata) to Azure
• Knowledge of data analytics and machine learning use cases
• Familiarity with DevOps practices and tools (e.g., Azure DevOps, Git)

What We Offer:

• Competitive salary and benefits package
• Opportunity to work on large-scale data projects and contribute to the development of cutting-edge data solutions
• Collaborative and dynamic work environment
• Professional development and growth opportunities