📍
Seattle, WA

Software Engineer - Systems PhD Candidates

1 year experience
Technology & Digital
Software engineering
Posted:
December 29, 2025

Databricks

Data intelligence platform for businesses
77.5
Palpable Score
Apply >view company >

At Databricks, we are passionate about helping data teams solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

We're radically simplifying the entire data lifecycle, from ingestion to generative AI and everything in-between. We’re doing it cross-cloud with a unified platform, currently serving over 10k customers, processing exabytes of data/day on 15+ million VMs, and growing exponentially.

To make it happen we’re building multi-cloud systems at every corner of the data ecosystem, from query engines, vector databases, training pipelines, and storage systems, down to the infrastructure that allows them to scale like auto-sharders, caches, and load balancers, just to name a few. We also build and support the tooling, languages, and stacks that bring it together. Basically, we do it all.

The space we work in and the problems we solve are massive, complex, and very deep (our published work on Lakehouse, Delta lake, and Photon are a testament to that). We’re looking for practitioners who are eager to work with the best in industry to push the boundaries of what’s possible for our customers. If you’re truth seeking, data driven, and love to operate from first principles (head fake: our core values), then Databricks is the place for you.

As a part of the Database Engine team, there are opportunities to design and implement in many areas that leapfrog existing state-of-the-art systems:

What we look for:

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

$142,500—$180,500 USD

About the company

Databricks

Company overview
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.

Locations and presence

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.

Palpable Score

77.5
/ 100
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.
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