Solutions Architect - Kansai Region
DatabricksJapanPosted 24 February 2026
Job Description
<p>P-1372</p>
<p>As a Pre‑sales Solutions Architect (Analytics, AI, Big Data, Public Cloud) – Kansai Region, your mission will be to drive successful technical evaluations and solution designs for some of our focus customers in the Kansai region (Osaka/Kyoto) for Databricks Japan. You are passionate about data and AI, love getting hands‑on with technology, and enjoy communicating its value to both technical and non‑technical stakeholders. Partnering closely with Account Executives, you will lead the technical discovery, architecture design, and proof‑of‑concept phases, and act as a trusted advisor to our customers on their data and AI strategy. You will help customers realize tangible, data‑driven outcomes on the Databricks Lakehouse Platform by guiding data and AI teams to design, build, and operationalize solutions within their enterprise ecosystem. You will also be a key technical voice back into our product and field teams, championing customer needs from the Kansai market. You will report to the Manager of Field Engineering.</p>
<p><strong>The impact you will have:</strong></p>
<ul>
<li>You will be a Big Data Analytics expert on aspects of architecture and design</li>
<li>Lead your prospects through evaluating and adopting Databricks</li>
<li>Support your customers by authoring reference architectures, how-tos, and demo applications</li>
<li>Integrate Databricks with 3rd-party applications to support customer architectures</li>
<li>Engage with the technical community by leading workshops, seminars and meet-ups</li>
<li>Together with your Account Executive, you will form successful relationships with clients throughout your assigned territory to provide technical and business value</li>
</ul>
<p><strong>What we look for:</strong></p>
<ul>
<li>Pre-sales or post-sales experience working with external clients across a variety of industry markets</li>
<li>Understanding of customer-facing pre-sales or consulting role with a core strength in either Data Engineering or Data Science advantageous</li>
<li>Experience demonstrating technical concepts, including presenting and whiteboarding</li>
<li>Experience designing and implementing architectures within public clouds (AWS, Azure or GCP)</li>
<li>Experience with Big Data technologies, including Apache Spark™, AI, Data Science, Data Engineering, Hadoop, Cassandra, and others.</li>
<li>Fluent coding experience in Python or Scala implementing Apache Spark™, Java and R is also desirable</li>
<li>Experience working with Enterprise Accounts</li>
<li>Written and verbal fluency in Japanese</li>
</ul>
<p> </p><div class="content-conclusion"><p><strong>About Databricks</strong></p>
<p><span style="font-family: arial, sans-serif;">Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on <span style="color: rgb(255, 54, 33);"><a style="color: rgb(255, 54, 33);" href="https://twitter.com/databricks" target="_blank" data-saferedirecturl="https://www.google.com/url?q=https://twitter.com/databrickssource=gmailust=1700237575733000usg=AOvVaw03FL8fJvOD97ytN02f5G2C">Twitter</a>, <a style="color: rgb(255, 54, 33);" href="https://www.linkedin.com/company/databricks" target="_blank" data-saferedirecturl="https://www.google.com/url?q=https://www.linkedin.com/company/databrickssource=gmailust=1700237575733000usg=AOvVaw15dLk3q8VxTfHEgCUg7NSt">LinkedIn</a> <span style="color: rgb(0, 0, 0);">and</span> <a style="color: rgb(255, 54, 33);" href="https://www.facebook.com/databricksinc" target="_blank" data-saferedirecturl="https://www.google.com/url?q=https://www.facebook.com/databricksincsource=gmailust=1700237575 ... (truncated, view full listing at source)
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