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Databricks Software Jobs (NOW HIRING)

Databricks

Senior Software Engineer - Backend

Bellevue, WA · On-site

$157K - $213K/yr

As a software engineer with a backend focus, you will work with your team to build infrastructure ... Build Databricks serverless platform that powers the big data, machine learning and Gen AI ...

Databricks

Senior Software Engineer - Money Team

Bellevue, WA · On-site

$138K - $182K/yr

P-1253 At Databricks, we are obsessed with Data + AI to solve the world's toughest problems, from ... As a Sr. Software engineer on the Money team, you will be closely involved in the entire billing ...

Databricks

Sr Software Engineer-Networking

Bellevue, WA · On-site

$157K - $213K/yr

(P-1286) At Databricks, we are passionate about enabling data teams to solve the world's toughest ... We are seeking experienced Senior Software Engineers with large-scale distributed system experience ...

Databricks

Staff Software Engineer - Streaming

Seattle, WA · On-site

$182K - $247K/yr

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems ... Raise the bar for engineering quality and operability, building software that is not just high ...

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Databricks Software information

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$48K

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How much do databricks software jobs pay per year?

As of Aug 3, 2026, the average yearly pay for databricks software in the United States is $111,845.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,000.00 and $130,000.00 per year, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Senior software engineers, especially those working in high-demand fields like data engineering or cloud engineering at large tech companies, can earn $500,000 or more annually. These roles often require extensive experience, advanced skills in programming and cloud platforms, and may include bonuses or stock options that contribute to total compensation.

What is Databricks Software?

Databricks Software is a unified analytics platform built on Apache Spark that provides tools for big data processing, machine learning, and collaborative data science. It enables organizations to store, manage, and analyze large datasets efficiently, supporting both batch and streaming data workloads. Databricks also offers collaborative notebooks, automated workflows, and integrations with cloud storage and data lakes, making it a popular choice for data engineering, data science, and business analytics teams.

How much do Databricks employees make?

Salaries for Databricks software roles vary based on experience, location, and specific position, but the average annual salary for software engineers at Databricks typically ranges from $100,000 to $150,000. Senior roles and specialized skills in data engineering or cloud platforms can command higher compensation. Benefits often include stock options, bonuses, and professional development opportunities.

Is Databricks a high paying job?

Working as a Databricks software engineer or data scientist typically offers above-average salaries compared to other tech roles, reflecting the specialized skills in cloud platforms, big data, and Spark. Compensation varies based on experience, location, and certifications, but generally includes competitive base pay, bonuses, and stock options. These roles often require knowledge of programming languages like Python or Scala and familiarity with cloud environments such as AWS or Azure.

What are some common challenges faced by Databricks Software Engineers, and how can they be overcome?

Databricks Software Engineers often encounter challenges related to scaling big data pipelines, optimizing Spark workloads, and integrating diverse data sources. Navigating the complexity of distributed systems and managing cloud infrastructure can be demanding, especially when ensuring data reliability and security. To overcome these challenges, engineers typically collaborate closely with data scientists, DevOps, and platform teams, leverage Databricks' extensive documentation and community support, and adopt best practices such as version control and continuous integration. Regular knowledge sharing and staying updated with new features also help engineers succeed in this dynamic environment.

What are the key skills and qualifications needed to thrive as a Databricks Software Engineer, and why are they important?

To thrive as a Databricks Software Engineer, you need strong programming skills in languages like Python, Scala, or Java, as well as a solid understanding of distributed computing and data engineering concepts. Familiarity with Databricks platform, Apache Spark, cloud services (such as AWS or Azure), and relevant certifications like Databricks Certified Data Engineer are highly valued. Excellent problem-solving abilities, collaboration, and effective communication are important soft skills for this role. These skills ensure efficient development, deployment, and optimization of big data solutions that drive business insights and innovation.

What exactly are Databricks Jobs?

Databricks Jobs are automated tasks or workflows that run on the Databricks platform, typically involving data processing, machine learning, or analytics tasks. They can be scheduled, monitored, and managed through the Databricks workspace, requiring knowledge of Spark, SQL, or Python scripting. Job roles often involve configuring clusters and ensuring efficient execution of data pipelines.

What is the difference between Databricks Software vs Data Engineer?

AspectDatabricks SoftwareData Engineer
Primary RolePlatform for data analytics and machine learningBuilds, maintains data pipelines and infrastructure
Required SkillsSQL, Spark, cloud platforms, data science basicsSQL, ETL, programming (Python, Scala), database management
Work EnvironmentCloud-based, collaborative data platformData teams, cloud or on-premises environments
CertificationsDatabricks certifications, cloud certificationsNone specific, often cloud or data certifications

While Databricks Software provides a platform for data analytics and machine learning, Data Engineers focus on building and maintaining data pipelines and infrastructure. Both roles often work together but have distinct responsibilities and skill sets within the data ecosystem.

More about Databricks Software jobs
What cities are hiring for Databricks Software jobs? Cities with the most Databricks Software job openings:
What states have the most Databricks Software jobs? States with the most job openings for Databricks Software jobs include:
What job categories do people searching Databricks Software jobs look for? The top searched job categories for Databricks Software jobs are:
Databricks Software jobs near you
Infographic showing various Databricks Software job openings in the United States as of July 2026, with employment types broken down into 5% Locum Tenens, 15% As Needed, 75% Full Time, 1% Part Time, and 4% Contract. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution, with an average salary of $111,845 per year, or $53.8 per hour.

Staff Software Engineer, Metrics and Logging

Databricks

Mountain View, CA • On-site

Other

Re-posted 27 days ago

Job description

RDQ426R299


At Databricks, we are passionate about enabling data teams to 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 tackle 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.

The Logging Platform team plays a critical role in building scalable and efficient logging solutions that power observability across all Databricks services. As a Staff Software Engineer, you will drive the next generation of our logging infrastructure, enabling engineers across the company to gain deep insights into system behavior, troubleshoot issues efficiently, and optimize performance at scale.

The impact you'll have:

  • Build the future of logging at Databricks by designing and scaling our next-generation logging platform that processes petabytes of logs daily.
  • Develop and optimize log delivery pipelines to support low-latency, high-throughput log ingestion and querying, ensuring seamless observability across all Databricks services.
  • Enhance log accessibility and usability, developing tools that enable engineers to efficiently search, analyze, and derive insights from logs.
  • Collaborate with teams across Databricks to define best practices for structured logging, standardizing formats and improving the developer experience.
  • Improve reliability and cost-efficiency by optimizing log retention, indexing, and query performance to reduce operational overhead.
  • Mentor and uplevel engineers, fostering a culture of technical excellence within the team and broader observability community.

What we look for:

  • BS (or higher) in Computer Science, or a related field.
  • 7+ years of production-level experience in one of: Scala, Rust, Go, Python, Java, C++, or similar languages.
  • Deep experience in software development, in large-scale distributed systems.
  • Experience driving complex projects involving multiple teams and stakeholders.
  • Familiarity with log collection, health monitoring, and observability tools.

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