> Markdown version of [/jobs/ext/159836-sr-software-engineer-performance](https://www.wearedevelopers.com/jobs/ext/159836-sr-software-engineer-performance). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Software Engineer - Performance - **Company:** Databricks - **Location:** Mountain View, CA, United States - **Experience:** Expert - **Salary:** $166,000.0 - $225,000.0 - **Contract:** Permanent contract - **Skills:** Computing Platforms, Distributed Systems, Cloud Services, Software Engineering, Virtual Machines, Information Technology, Low Latency, Databricks - **Published:** May 31, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=8a1c267ccf298914 ## About the Role Do you have experience in Employee relationship building?, Do you have a Bachelor's degree?, * BS (or higher degree) in Computer Science, or a related field * Experience in the performance analysis discipline. Ability to identify performance issues, root cause problems, and be able to come up with potential solutions. * Experience in software development, preferably in large scale distributed systems * Ability to measure and document the impact of performance features to existing customers, such as possible regressions for certain workloads, their extent, and which customers will be affected. * Ability to build strong working relationships with developers and field engineers to facilitate triaging and mitigation of performance problems. Pay Range Transparency ## Description At Databricks, we are passionate about enabling data teams to solve the world's toughest problems. 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. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform. Databricks develops and operates one of the largest scale software platforms; the fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. As a performance engineer, you will work closely with multiple teams across the company to evaluate the performance of products and features, identify performance bottlenecks, and partner with engineers to solve performance and scalability issues. This implies, among other teams, setting performance targets for various software releases, guiding teams to develop performance benchmarks, running competitive benchmark analysis for different Databricks products, doing deep dive analysis to identify performance issues and fix them. The impact you will have: * Identify performance limitations of the entire stack based on telemetry, customer signals, PoCs, and competitive benchmarks, that will result in the best performing system across the industry, when resolved. Dimensions include latency, data and compute scalability, concurrency, cost, and price to performance ratio. Impact spans all cloud providers and all major areas. * Set the performance expectations for all cross-cutting efforts early on through specialized benchmarks capturing the intended customer user journeys, and make sure they are met before deployed to customers. * Understand the performance characteristics of the compute instance types, storage layers, and all cloud services Databricks depends on and deploy optimal solutions to meet the customer demand. * Work with customers to root cause and mitigate performance problems during production, previews, and POCs. ## Related Videos - [How building an industry DBMS differs from building a research one](https://www.wearedevelopers.com/videos/768-how-building-an-industry-dbms-differs-from-building-a-research-one) - [Leverage Cloud Computing Benefits with Serverless Multi-Cloud ML ](https://www.wearedevelopers.com/videos/78-leverage-cloud-computing-benefits-with-serverless-multi-cloud-ml) - [Swapping Low Latency Data Storage Under High Load](https://www.wearedevelopers.com/videos/746-swapping-low-latency-data-storage-under-high-load) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [How Much Does a Software Engineer Make? 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