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Hiring now · posted 97d ago Science Full-time · Remote

Sr. Solutions Architect - Digital Native Business, Strategics

at Databricks

Pay not published

The rate is shared during the application.

Remote · United States Language: English Posted 22 Jul 2026

About this role

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As a Sr. Solutions Architect on the team supporting the strategic Digital Natives Business (DNB) customers, you will shape the future of the Data & AI landscape by working with the most sophisticated data engineering and data science teams in the world.

Reporting to the Field Engineering Manager, you will collaborate with customers, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide customers through the competitive landscape, best practices, and implementation, and develop technical champions along the way.

The impact you will have:

  • You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems.
  • Lead technical discovery and design architectures, implement proof of concepts for strategic projects spanning data engineering, data science and machine learning, and SQL analysis workflows. You will also help customers build solutions that integrate with cloud services, home grown tools, and other 3rd party applications.
  • Act as strategic technical advisor to customers to help them drive business outcomes.
  • Collaborate with your fellow Solutions Architects, using your skills to support each other and our users.
  • Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, MLflow, Omnigent) across the developer community.

What we look for:

  • 7+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role
  • Experience building distributed data systems
  • Comfortable programming in and debugging Python and SQL
  • Have built solutions with public cloud providers such as AWS, Azure, or GCP
  • Expertise in one of the following:
    • Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
    • Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, PyTorch, Tensorflow)
  • Available to travel to customers in your region
  • [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
  • Nice to have: Databricks Certification
  • Location: Remote (Pacific Time preferred; Mountain Time considered).

NOTE: If your experience isn’t a perfect match for the job description, but you feel like you’re a good fit for the role, apply.  We want to work with smart, passionate, people who are good at their job, and, a lot of times, those people have non-linear career paths.

 

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.

 

Local Pay Range$219,100—$301,300 USD

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.

This is a remote role. Applicants must be located in: United States.

How applying works

  1. Click Apply now and enter your email.
  2. You go straight to the application. We email you a copy of this role and your link.
  3. You apply on Databricks's own careers page. Zekai is not the employer and never charges you.
How to get this job

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What to know before you apply

Location
Only applicants located in United States can be paid for this role. Platforms usually verify where you are, so apply only if you are based there.
Credentials
The listing asks for an active professional licence, 7+ years of experience. Put it in the first line of your profile: reviewers screen for it before anything else.
How to stand out for sales teams
  • Mirror the job's own wording in your CV: reviewers and screening tools look for the skills listed above.
  • Show real work: a portfolio, GitHub, case study or numbers from past projects beats a long list of duties.
  • Show how you already use AI tools in your work. AI companies hire people who use their products well.
  • Apply early and follow up once, politely, if you hear nothing in two weeks.
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