Teams at Ultra Tendency

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.