Solutions Architect (Pre-sales) – Manufacturing & Automotive

Databricks
Tokyo
Workplace: OnsiteFull timeFunction: Solutions Engineering & Sales EngineeringSkills: ["Communication","Presentation","Storytelling","Stakeholder management","Cross-functional collaboration","Relationship building","Whiteboarding","Coaching","Mentoring","Influencing decision-makers"]

Engage with automotive and manufacturing customers across Japan to drive adoption of the Databricks Data Intelligence Platform. Lead technical pre-sales from discovery and solution scoping through architecture design, workshops, demos, and proof-of-concepts. Build tailored demos, prototypes, and migration plans using Databricks and public cloud platforms (AWS, Azure, GCP), translating connected-vehicle, smart manufacturing, supply-chain, and AI use cases into measurable outcomes.

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FursaFursa
Databricks
Databricks
3 days ago

Solutions Architect (Pre-sales) – Manufacturing & Automotive

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 10 hours agoStatus: Live
Reposted: similar role first listed 1 month ago

Job Summary

Engage with automotive and manufacturing customers across Japan to drive adoption of the Databricks Data Intelligence Platform. Lead technical pre-sales from discovery and solution scoping through architecture design, workshops, demos, and proof-of-concepts. Build tailored demos, prototypes, and migration plans using Databricks and public cloud platforms (AWS, Azure, GCP), translating connected-vehicle, smart manufacturing, supply-chain, and AI use cases into measurable outcomes.
Location: Tokyo
Workplace: Onsite
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering

Key Responsibilities

  • •Develop and execute customer engagement strategies for strategic automotive and manufacturing accounts in partnership with Account Executives and other pre-sales stakeholders.
  • •Lead complex technical customer engagements across the full pre-sales lifecycle: discovery, requirements gathering, solution scoping, architecture design, workshops, demonstrations, proof-of-concepts, and implementation planning.
  • •Coach account teams and peers on positioning, adoption strategies, use-case prioritization, and execution plans to deliver outcomes within timelines.
  • •Design and communicate end-to-end solutions using Databricks and public cloud platforms (AWS, Azure, GCP), including tailored demos, prototypes, reference architectures, migration plans, and customer-facing materials.
  • •Lead technical workshops and community activities (workshops, seminars, meetups) to build technical awareness and scale best practices in Japan.

Key Requirements

  • •Experience in technical pre-sales, consulting, technical architecture, or an equivalent role with complex customer/sales lifecycles.
  • •Technical background in data engineering, data warehousing, machine learning, artificial intelligence, or related fields.
  • •Experience designing and implementing solutions on public cloud platforms, including AWS, Azure, or GCP.
  • •Hands-on expertise delivering complex proof-of-concepts and technical demonstrations.
  • •Ability to code in Python or SQL; willingness to learn or deepen knowledge of Apache Spark (Scala, Java, or R beneficial).
Experience:AutomotiveManufacturingData engineeringData warehousingMachine learningArtificial intelligenceGenerative AIPublic cloudEnterprise data platformsLakehouse
Skills:CommunicationPresentationStorytellingStakeholder managementCross-functional collaborationRelationship buildingWhiteboardingCoachingMentoringInfluencing decision-makers
Languages:JapaneseEnglish
Tech Stack:Databricks Data Intelligence PlatformAWSAzureGCPPythonSQLApache SparkScalaJavaRMLflowDelta LakeLakehouse architecturesPublic cloudDistributed data systemsMachine learningGenerative AIUnity CatalogGenieLakebase

Company Brief

Databricks
Provides a unified data analytics platform powered by Apache Spark to simplify building, deploying, and scaling data engineering, data science, and machine learning workloads for enterprises.
Industry: Data Infrastructure
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series E+
Headquarters: San Francisco, United States
Founded: 2013
WebsiteLinkedIn