Job Description

GAQ227R1

Work at the nexus of law and innovation with a recognized global leader in Data and AI. As a Databricks Legal Intern, you won’t just observe, you’ll jump straight into novel legal issues working alongside our high-impact global legal team. You will gain first-hand experience on how an in-house legal department drives business strategy and tackles complex challenges on a daily basis, and navigate cutting-edge legal landscape of generative AI, cloud computing, and big data. Databricks will encourage you to get out of your comfort zone and provide the resources, mentoring, and feedback you need to grow your legal skills and career.

This is a hybrid, in-person position located in our San Francisco and Mountain View offices. The position offers exposure to a variety of legal practice areas and allows for potential deep dives of areas including: Commercial and Go-to-Market, Privacy, IP, Product & Privacy, Legal Compliance & Ethics, Corporate, Employment & Litigation, and others. You and our other legal interns will work with mentors within Legal as well as join our summer 2026 intern cohort where you'll have the opportunity to connect with other interns, cross-functional teams and leaders not just within our department, but across the company.

The impact you will have:

• Work with various Databricks Legal teams to support all areas of our business
• Research and teach our Legal department about novel legal issues, especially as they relate to AI and cloud technology
• Further Legal strategy and objectives through the development of critical work product and/or assets that will inform future initiatives
• Contribute to mission-critical projects and initiatives across a variety of practice areas, including Commercial and Go-to-Market, Privacy, IP, Product & Privacy, Legal Compliance & Ethics, Corporate, Employment & Litigation, and others to gain broad exposure to our business and operations
• Help Databricks continue to balance legal risks as it continues on its exciting path forward

What we look for:

• Currently enrolled as a 1st-year (1L) or 2nd-year (2L) law student (graduating in summer 2027 or summer 2028), with a strong record of academic performance
• Eagerness to learn about Databricks technology and new legal issues
• Willingness to roll-up your sleeves and tackle tough problems with the full support of our team
• Excellent written and verbal communication skills
• Ability to work both independently and with colleagues as needed
• Exceptional legal research, analytical, and organizational skills, along with a strong foundation in advocacy and judgment
• High-level legal drafting skills that is consistent with current legal education and experience
• A desire to be part of a dynamic legal team supporting the recognized leader in processing big data in the cloud
• Prior background or strong interest in technology, data analytics and Artificial Intelligence (preferred but not required)

Additional Program Details:

• Internship program starts on June 8, 2026 and ends August 7, 2026
• Position is full-time (40 hours per week)
• This is a hybrid, in-person role, requiring a minimum of three days per week in our San Francisco or Mountain View offices
• Applications will be accepted on a rolling basis through mid- to late- February; interviews may begin as early as mid-January
• Application packages should include: resume, law school transcript, undergraduate transcript, law school writing sample, and a cover letter describing why you are interested in Databricks and this program

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 .

SF Bay Area Hourly Rate

$40—$40 USD

About Databricks

Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter LinkedIn and Facebook .

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, please visit .

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.

Job Tags

Hourly pay, Full time, Summer work, Summer internship, Worldwide, 3 days per week,

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