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Designs and maintains scalable Databricks data pipelines and batch or streaming workflows using Spark and Delta Lake. Collaborates with engineers, scientists, and architects to deliver production-ready data solutions, optimize processing performance and costs, and support data quality, governance, and security. The role also contributes to knowledge sharing and mentors junior engineers in an international, hybrid Tokyo-based environment.

Advise enterprise customers on Databricks-based data and AI transformations. Design and optimize Lakehouse architectures, data pipelines, governance, analytics, machine learning, and GenAI workloads. Lead architecture workshops, technical roadmaps, implementation support, executive presentations, and customer enablement. Mentor teams, resolve technical blockers, support presales and proposals, and develop reusable reference architectures and practice assets.

Lead and develop engineering teams, own delivery and performance outcomes, resolve risks and blockers, manage stakeholder expectations, support architecture and technical decisions, and promote quality, security, testing, CI/CD, documentation, and continuous improvement. The role also involves coaching engineers, strengthening engineering processes, and collaborating with distributed cross-functional teams.

Designs, builds, and maintains scalable Databricks Lakehouse data pipelines using Spark and Delta Lake. Develops batch and streaming workflows, optimizes performance and cost, and supports data quality, governance, security, and compliance. Collaborates with engineers, data scientists, architects, and stakeholders to deliver production-ready cloud data platforms. The role also contributes to architecture and platform strategy, mentors junior engineers, and supports client projects in agile environments.

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, roadmap discussions, technical delivery, executive presentations, and stakeholder engagements. Mentor teams, resolve technical blockers, support presales and proposals, and develop reusable architecture assets. The role requires strong Databricks expertise, cloud architecture experience, consulting skills, and fluent English and German.

Design, implement, and maintain scalable Databricks Lakehouse data pipelines using Apache Spark and Delta Lake. Develop and optimize batch and streaming workflows supporting analytics, machine learning, and BI applications. Collaborate with cross-functional teams to deliver production-ready data solutions, improve performance and cost efficiency, and promote data quality, governance, and security. Share knowledge and mentor junior engineers.

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, roadmap discussions, implementations, governance, security, and cost optimization efforts. Mentor teams, present to executives, support presales and proposals, resolve technical blockers, and develop reusable architecture assets while helping expand the Databricks consulting practice.

Serve as a senior technical advisor for enterprise Databricks customers across APJ and EMEA. Design, implement, and optimize Lakehouse data, analytics, machine learning, and GenAI architectures. Lead architecture workshops, technical roadmaps, governance, security, and platform optimization efforts. Mentor teams, present to executives, support presales and proofs of concept, resolve technical blockers, and develop reusable architecture assets. The role requires strong Databricks expertise, consulting skills, and English and Japanese communication abilities.

Designs, implements, and maintains scalable Databricks data pipelines and batch or streaming workflows using Spark and Delta Lake. The role optimizes data processing performance and costs, supports data quality, governance, and security, and collaborates with engineers, data scientists, architects, and clients. It also involves translating requirements into production-ready solutions, sharing knowledge, and mentoring junior engineers in an international environment.

Advise enterprise customers on Databricks data and AI transformations. Design, review, and optimize Lakehouse architectures, data platforms, governance, security, analytics, machine learning, and GenAI workloads. Lead architecture workshops, technical roadmaps, solution delivery, executive presentations, and customer enablement. Mentor teams, resolve technical blockers, support presales and proposals, and contribute to reusable consulting assets and practice development.