Scale Solution Engineer (Japanese-speaking; English required)

AI in this role

Provide technical onboarding and support to customers deploying data analytics and cloud solutions.

pythonscalasqlsparkairflowdbtawsazuregcpsnowflakeredshift

data-engineeringcustomer-successcloud-computingtechnical-supportetl

Req ID: CSQ327R200
Location: Tokyo, Japan

At Databricks, we aim to empower our customers to solve the world's most challenging data problems using the Data Intelligence platform. As a Scale Solution Engineer, you will be critical in advising customers during their onboarding. You will work directly with customers to help them onboard and deploy Databricks in their production environment.

The impact you will have:

You will ensure new customers have an excellent experience by providing technical assistance early in their journey
You will become an expert on the Databricks Platform and guide customers in making the best technical decisions
You will work directly with multiple customers concurrently to provide technical solutions.

What we look for:

Undergraduate degree or higher in Computer Science, Information Systems, or relevant experience
2+ years experience in a technical role, preferably in the data or cloud field
Knowledge of at least one of the public cloud platforms AWS, Azure, or GCP is required.
Knowledge of a programming language - Python, Scala, or SQL
Knowledge of end-to-end data analytics workflow
Hands-on professional or academic experience in one or more of the following:

Data Engineering technologies (e.g., ETL, DBT, Spark, Airflow)
Data Warehousing technologies (e.g., SQL, Stored Procedures, Redshift, Snowflake)

Excellent time management and prioritization skills
Bonus - Knowledge of Data Science and Machine Learning (e.g., build and deploy ML Models)
Excellent written and verbal communication in Japanese and English
Excellent time management and prioritization skills
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.

How we rate this

Scale Solution Engineer (Japanese-speaking; English required) at Databricks rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Data EngineeringCustomer SuccessCloud ComputingTechnical SupportETLPythonScalaSQL

Questions you could be asked

Tell me about a project where data engineering was part of your work. What did you do?
Tell me about a project where customer success was part of your work. What did you do?
Tell me about a project where cloud computing was part of your work. What did you do?
Tell me about a project where technical support was part of your work. What did you do?
Tell me about a project where etl was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Data Engineering, Customer Success, Cloud Computing, Technical Support, and ETL. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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