Location: North Carolina Experience: Not specified Job Type: Permanent
### Top Skills & Technologies Databricks | Unity Catalog | Lakehouse | PySpark | Airflow | Data Governance | Azure
### Job Summary Thinking Minds' client is seeking a Databricks technical lead to design enterprise-scale Lakehouse architectures and guide data platform modernization. This role combines architectural leadership with hands-on engineering, secure data management, and reusable solution development. The successful candidate will define target-state architectures, establish migration roadmaps, and translate enterprise requirements into scalable platform designs. The position follows an onsite/hybrid working arrangement in North Carolina.
### Ideal Candidate Should Have
• Strong architectural judgment and the ability to connect platform design decisions with business and operational needs.
• A hands-on approach to engineering, with confidence moving between architecture planning and implementation.
• Deep understanding of enterprise Data Governance, secure data sharing, and practical controls for large-scale environments.
• Clear communication skills for explaining architecture choices and promoting consistent engineering practices across teams.
### Key Responsibilities
• Design enterprise-scale Lakehouse solutions using Databricks, including target-state architectures and migration roadmaps.
• Develop reference architectures, reusable frameworks, and accelerators that support consistent delivery and platform adoption.
• Establish data governance, security, and operational standards across the platform lifecycle.
• Implement role-based access controls, data masking, and governance models with Unity Catalog, supporting classification, lineage, auditability, and secure sharing.
• Develop and implement PySpark jobs and incorporate orchestration approaches using tools such as Airflow.
• Apply advanced platform capabilities, including Databricks Apps and Delta sharing, and support real-time and streaming integration.
### Required Qualifications
• Demonstrated capability in enterprise data architecture and Databricks platform implementation.
• Strong knowledge of Unity Catalog and governance practices for large-scale data environments.
• Hands-on experience developing and implementing PySpark workloads.
• Background working with orchestration tools such as Airflow.
• Knowledge of real-time data integration, streaming patterns, access management, and secure data sharing.
### Preferred Qualifications
• Familiarity with CI/CD methods for reliable deployment and maintainable data engineering workflows.
• Experience applying Azure services within enterprise data platform architectures.
• Interest in enabling governed data foundations for Generative AI use cases.
Thinking Minds' client offers a collaborative environment, opportunities to shape enterprise data platforms, and benefits subject to applicable policy and eligibility.
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