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Designs and maintains scalable Databricks Lakehouse data pipelines using Spark and Delta Lake. Develops batch and streaming workflows, optimizes performance and costs, and supports data quality, governance, security, and compliance. Collaborates with engineers, scientists, architects, and business stakeholders to deliver production-ready solutions. Contributes to data platform strategy, works in agile environments, and mentors junior engineers.

Advise enterprise customers on Databricks data and AI transformations. Design, review, and optimize Lakehouse architectures, data pipelines, governance, security, analytics, machine learning, and GenAI workloads. Lead architecture workshops, technical roadmaps, implementation support, executive presentations, and customer enablement. Mentor teams, resolve technical blockers, develop reusable assets, and support pre-sales, proposals, proof-of-concepts, and expansion opportunities.

Design, implement, and maintain scalable batch and streaming data pipelines using Databricks, Apache Spark, and Delta Lake. Build production-ready data platforms supporting analytics, machine learning, and business intelligence applications. Collaborate with cross-functional teams to translate requirements into reliable solutions, optimize performance and costs, and promote data quality, governance, and security best practices. Contribute to knowledge sharing and mentor junior engineers in an international consulting environment.

Designs, builds, and maintains scalable Databricks Lakehouse data pipelines and batch or streaming workflows. Optimizes data processing performance, scalability, and cost while supporting analytics, machine learning, and business intelligence use cases. Collaborates with engineers, architects, data scientists, and stakeholders to deliver production-ready platforms. Contributes to data quality, governance, security, compliance, and architecture, while mentoring junior engineers and supporting client-focused data platform strategies.

Serve as a senior technical advisor for enterprise Databricks customers across APJ and EMEA. Design, review, and optimize Lakehouse, data engineering, analytics, machine learning, and GenAI architectures. Lead workshops, technical roadmaps, platform adoption, governance, security, and cost optimization efforts. Mentor teams, present to executives, support presales and proposals, resolve technical blockers, and develop reusable architectures and best practices.