Lead the technical strategy and delivery of cutting-edge Databricks-centric data platforms. You will be instrumental in connecting business needs with robust technical architecture, ensuring a scalable, cost-effective (FinOps), and seamlessly integrated Databricks ecosystem within the broader Azure data landscape.

This role demands expertise in architecting and implementing enterprise-grade data solutions, with a focus on modern data modernization and migration initiatives.

Architect large-scale data platforms using Databricks. Define and enforce technical standards for data modeling, Spark optimization, and coding. Drive Databricks FinOps through efficient cluster policies and resource optimization. Lead integration with Azure Synapse, Power BI, and advanced Machine Learning workflows. Oversee enterprise data governance and security frameworks. Manage technical project delivery, ensuring business alignment and quality.

A minimum of 7-10 years in data engineering, with substantial experience architecting solutions on Azure Databricks and designing end-to-end Data Lakehouse architectures. Proven expertise in Databricks FinOps, including DBU consumption and cluster policy management. Strong leadership experience managing technical teams and project lifecycles is essential.

Preferred qualifications include a Bachelor's or Master's degree in Computer Science or a related field, along with relevant Databricks or Azure Solutions Architect certifications.