Synced from Greenhouse · Sep 11

Solution Engineer

DatabricksHeredia, Costa RicaPosted Sep 11, 2026
Solutions EngineerMid
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Mirrored from Databricks's own Greenhouse careers system · refreshed hourly

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Sep 11
Posted
Greenhouse
Applicant system
Job descriptionReq 8779023002

CSQ327R201

At Databricks, we aim to empower our customers to solve the world's most challenging problems using the Data + AI Platform while putting trusted data and AI in the hands of every business user. As a Scale Solution Engineer, you play a critical role in advising customers across many stages of their lifecycle: from pre-sales evaluation through onboarding and into production, by building and working with AI-augmented workflows that enable one engineer to deliver quality guidance at scale.

The impact you will have:

  • You will ensure customers have an excellent experience by providing technical assistance across their lifecycle.
  • You will become an expert on the Databricks Data + AI Platform and guide customers in making the best technical decisions through AI-augmented workflows.
  • You will work directly with multiple customers concurrently to provide technical solutions.

What we look for:

  • Excellent communication and interpersonal skills, with the ability to assess customer needs, foster relationships, address objections, and effectively showcase the value of the Databricks Data + AI Platform.
  • Undergraduate degree or higher in Computer Science, Information Systems, or similar relevant experience.
  • 1+ years of experience in a technical role, preferably in the Data, AI, or Cloud field.
  • Knowledge of at least one of the following cloud platforms, AWS, Azure, or GCP, is required.
  • Knowledge of AI-driven development with programming languages like Python or SQL.
  • Understanding of the end-to-end data analytics and data engineering workflow.
  • Excellent time management and prioritization skills.
  • Bonus: Experience in consulting or pre-sales roles, or with agentic solutions.

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.

View original posting on Greenhouse

What applying to Databricks usually looks like

Based on publicly available information, candidates applying through greenhouse for roles at Databricks can generally expect a structured process typical of this ATS. This commonly begins with an online application and resume screen, followed by a recruiter conversation to discuss background and role fit. Depending on the position, candidates may encounter technical assessments, take-home exercises, or case studies, particularly for engineering, data, and analytical roles. The process may include multiple stages such as hiring manager conversations, panel discussions, and team or cross-functional interviews. Response times vary and communication is typically managed through the greenhouse platform, including scheduling and status updates. Candidates should prepare to discuss relevant experience, technical skills, and role-specific scenarios, as greenhouse-based processes commonly emphasize structured evaluation criteria across candidates to support consistent, comparative hiring decisions throughout the pipeline.

Based on publicly available information. LandEarly does not verify interview process details.

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Solution Engineer
Databricks · Heredia, Costa Rica
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