Databricks Solution Architect

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Databricks Solution Architect

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Job Info

• Job Identification15197
• Posting Date07/01/2026, 04:49 PM
• Job RoleData Management and Analytics-Database Warehousing
• Experience (In Years)9-12
• Job LocationRemote

Job Description

We are seeking an experienced Databricks Architect to lead the design and implementation of scalable data platforms on Databricks. The role will drive end-to-end architecture, including data ingestion, transformation, optimization, and governance, while enabling advanced analytics and AI/ML use cases. The ideal candidate will have strong expertise in Spark, Delta Lake, cloud platforms (Azure/AWS), and modern data engineering practices, along with the ability to collaborate with business and technology stakeholders to deliver high-impact solutions.

Responsibilities

• Lead the design and implementation of scalable, secure, and high-performance data architecture on Databricks
• Define end-to-end data pipelines (ingestion, transformation, serving) using Spark and Delta Lake
• Drive migration and modernization initiatives from legacy platforms to Databricks
• Establish best practices for data engineering, performance optimization, and cost management
• Design and implement data governance, security, and compliance frameworks
• Collaborate with business stakeholders, data scientists, and engineering teams to translate requirements into technical solutions
• Provide technical leadership, mentorship, and guidance to development teams
• Ensure data quality, reconciliation, and reliability across data workflows
• Integrate Databricks with enterprise tools (e.g., MuleSoft, Alteryx, BI/reporting platforms)
• Stay current with Databricks innovations and recommend adoption of new capabilities (e.g., ML, AI, DBSQL, Unity Catalog)

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
• 9-12+ years of experience in data engineering, data architecture, or analytics platforms
• Strong hands-on expertise with Databricks, Apache Spark, and Delta Lake
• Experience with cloud platforms such as Azure (preferred), AWS, or GCP
• Proven experience designing and implementing scalable data pipelines and architectures
• Strong knowledge of SQL, Python, and/or Scala
• Experience with data integration tools (e.g., MuleSoft, Alteryx) and modern data ecosystems
• Familiarity with data governance, security frameworks, and compliance best practices
• Experience with performance tuning, optimization, and cost management in Databricks
• Strong problem-solving skills and ability to work in a cross-functional, collaborative environment
• Excellent communication and stakeholder management skills
• Exposure to AI/ML use cases, Databricks SQL, and Unity Catalog is a plus

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