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Specialist Solutions Architect (Data Warehousing)

Databricks

Engineering Japan / Tokyo, Japan

Employer posted: October 13, 2026. Source checked: October 18, 2026 6:16 pm. Availability and final application requirements are confirmed on the employer’s site.

Source: Databricks — company careers. WorkerEra lists this opportunity from an external source; confirm current details with the employer.

About this opportunity

Req: FEQ427R624
Location: Tokyo, Japan
Language Requirements: Fluent Japanese required; Business-level English preferred 

As a Specialist Solutions Architect (SSA) – Data Warehousing, you will guide customers in their cloud data warehousing transformation with Databricks which span a large variety of use cases. You will be in a customer-facing role, working with and supporting Solution Architects, that requires hands-on production experience with large-scale data warehousing technologies and lakehouse architecture. SSAs help customers through evaluations and successful production planning for their business intelligence workloads while aligning their technical roadmap for the Databricks Data Intelligence Platform. As a deep go-to-expert reporting to the Specialist Field Engineering Manager, you will continue to strengthen your technical skills through mentorship, learning, and internal training programs and establish yourself in the data warehousing specialty – including performance tuning, data modeling, winning evaluations, architecture design, and production migration planning.

The impact you will have:

  • Provide technical leadership to guide strategic customers to successful cloud transformations on large-scale data warehousing workloads – ranging from evaluation to architecture design to production deployment
  • Prove the value of the Databricks Intelligence Platform for customer workloads by architecting production workloads, including end-to-end pipeline load performance testing and optimization
  • Become a technical expert in an area such as data warehousing evaluations or helping set up successful workload migrations
  • Assist Solution Architects with more advanced aspects of the technical sale including custom proof of concept content, estimating workload sizing and performance, and tuning workloads for production
  • Provide tutorials and training to improve community adoption (including hackathons and conference presentations)
  • Contribute to the Databricks Community

What we look for:

  • 5+ years experience in a technical role with expertise in data warehousing – such as query tuning, performance tuning, troubleshooting, query conversion, debugging MPP data warehouses or other big data solutions, or migration workloads from EDW or other systems
  • Experience with design and implementation of data warehousing technologies including relational databases, SQL, data analytics,, MPP, and OLAP
  • Deep Specialty Expertise in at least one of the following areas:
    • Experience scaling large analytical data warehouse workloads in the cloud that are performant and cost-effective
    • Maintained, extended, or migrated a production data warehouse system to evolve with complex needs, including data modeling, data governance needs, and integration with business intelligence tools
    • Experience migrating on-premise EDW workloads to the public cloud
  • Bachelor’s degree in Computer Science, Information Systems, Engineering, or equivalent experience through work experience
  • Production programming experience in SQL and Python, or Java for developing UDFs
  • Experience with the AWS, Azure, or GCP clouds
  • 2 years professional experience with data warehousing and big data technologies (Ex: SQL, Redshift, SAP, Synapse, Snowflake, OLAP & OLTP workloads)
  • 2 years customer-facing experience in a pre-sales or post-sales role
  • Can meet expectations for technical training and role-specific outcomes within 6 months of hire
  • Bachelor’s degree in Computer Science, Information Systems, Engineering, or equivalent work experience
  • Fluent proficiency in Japanese is a must, and business-level English is preferred
  • Nice to have: Databricks Certification

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer’s discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Imported source listing. Details are supplied by the source and have not been independently verified by WorkerEra. Confirm the current vacancy on the employer’s page.

Source: Databricks — company careers

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  • Read the linked employer announcement and compare its requirements with your experience.
  • Tailor your CV to responsibilities and skills actually listed by the employer.
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  • Salary was not supplied in the listing fields; ask the employer about compensation.

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