Databricks builds a cloud platform used by data teams to run analytics, data engineering, and AI workloads in one place, often described as a “lakehouse” approach. The company sells to enterprises that want to unify data pipelines, BI, and machine learning on major clouds. Databricks is closely associated with Apache Spark’s origins and supports open-source projects used widely in data engineering and ML workflows. The company’s customers range from large enterprises to fast-growing tech companies building data products.

Databricks is headquartered in San Francisco and lists many offices across the Americas, EMEA, and Asia-Pacific. The company describes a hybrid setup built around weekly “Team Day” in-office time, with most work happening from home, and notes that some roles are fully remote.

Databricks offers clear, recurring entry points for students and new grads, and the company backs that up with cohort-style roles and explicit mentorship language in early-career job postings. Databricks also publishes candidate-facing guidance on the hiring process and shares pay bands on at least some early-career roles, which is a practical signal of transparency. The main limiter is mixed public candidate and employee feedback on consistency, especially around responsiveness and clarity of progression, and the lack of published early-career outcomes data.