Threat Intel Manager Jobs

P-1107 At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions. Customers trust Databricks with their most valuable data, and Trust & Safety has the mission to build the most trusted Data and AI platform in the world. Identity and Access Management (IAM) is at the heart of this mission, ensuring that the right users and services have the right access at the right time. We are looking for an Engineering Manager to lead our IAM team and define the strategy for how authentication, authorization, and identity services are built and scaled across our platform. You will lead a team owning foundational services that must be highly reliable, secure, and fast under extreme load. The impact you will have: Define and drive the strategy for IAM systems, including authentication and access control. Build and scale a high-performing engineering team focused on authentication, authorization, and identity management at cloud scale. Provide technical oversight on architecture and design for IAM components that can operate at massive scale, with high requirements for reliability, security, and performance. Partner with engineering and product leaders across Databricks to embed secure, scalable identity solutions into every aspect of our product. Ensure regulatory compliance and alignment with industry best practices for IAM, helping customers meet their own governance, privacy, and security needs. Attract and grow top engineering talent, building a team culture that emphasizes innovation, collaboration, and customer trust. What we look for: 9+ years of professional experience in software engineering, with 2+ years of engineering leadership experience in a fast paced, dynamic environment. Experience buildin

RDQ127R9 At Databricks, we are obsessed with Data + AI to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions. Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, CA to a global organization with over 6500 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest-growing SaaS companies in the world. The Money team's mission at Databricks is to maximize the value that our customers derive from their investments in data projects. We accomplish this through innovative commercialization strategies and cutting-edge engineering. Our team ensures timely, accurate, and customizable billing and usage data, alongside budgeting, forecasting, and cost optimization tools. We provide a seamless and consistent billing experience for all our customers, whether they are large enterprises or individual developers, across different pricing plans and cloud providers (AWS, GCP & Azure). As a Sr. Staff Software Engineer on the Money team, you will be closely involved in the entire billing process, including usage ingestion, metering, pricing, credits, promotions, payments, usage reporting, and cost center and budgeting. Your role is crucial in democratizing data by bringing Databricks products to market. By collaborating with marketing, product teams, commercialization experts, data scientists, IT, and customer support, you will standardize billing experiences across major cloud providers, offering our customers a unified "sky computation" experience. This role involves utilizing the latest Databricks products and tools within the ecosystem. The impact you will have: Design and manage the Money system

Our Security team keeps Asana's employees, users, and customers safe by proactively addressing threats and fostering a culture of security across our product and operations. We're looking for a Staff Detection Engineer to join our Threat Response team in our Warsaw innovation hub. You'll own how we find threats: the detection logic, the telemetry it runs on, and the pipeline that ships it. Detection here is software. Rules are written as code, tested against real and synthetic attacker behavior, reviewed in pull requests, and deployed through CI/CD. You'll partner with our incident responders, infrastructure, and product teams to make sure that when something bad happens, we see it fast and with high signal. We offer a Contract of Employment (UoP) for our employees in Poland. What you'll achieve Design, build, and maintain high-fidelity detections across cloud infrastructure (AWS/GCP), identity providers (e.g., Okta), SaaS environments, endpoints, and the software supply chain. Own our detection-as-code pipeline in Panther: rule structure, unit and integration tests, review standards, and CI/CD deployment, so detection logic is treated as production code. Map and close coverage gaps against MITRE ATT&CK and the threat model for our environment, prioritizing the techniques most likely to be used against a SaaS company. Onboard and normalize new telemetry sources , working with infrastructure and IT to make sure the right logs exist, are complete, and are queryable. Measure and improve alert quality , tracking precision, time-to-triage, and false-positive rates, and tuning or retiring detections that don't earn their keep. Validate detections against real attacker behavior through purple-team exercises, atomic tests, and emulation, and feed findings back into rule development. Turn incidents and threat intelligence into detections , partnering with incident responders to convert lessons learned and emerging TTPs into durable coverage. Build enrichment and automati

P-1253 At Databricks, we are obsessed with Data + AI to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions. Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, CA to a global organization with over 6500 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest-growing SaaS companies in the world. The Money team's mission at Databricks is to maximize the value that our customers derive from their investments in data projects. We accomplish this through innovative commercialization strategies and cutting-edge engineering. Our team ensures timely, accurate, and customizable billing and usage data, alongside budgeting, forecasting, and cost optimization tools. We provide a seamless and consistent billing experience for all our customers, whether they are large enterprises or individual developers, across different pricing plans and cloud providers (AWS, GCP & Azure). As a Sr. Software engineer on the Money team, you will be closely involved in the entire billing process, including usage ingestion, metering, pricing, credits, promotions, payments, usage reporting, and cost center and budgeting. Your role is crucial in democratizing data by bringing Databricks products to market. By collaborating with marketing, product teams, commercialization experts, data scientists, IT, and customer support, you will standardize billing experiences across major cloud providers, offering our customers a unified "sky computation" experience. This role involves utilizing the latest Databricks products and tools within the ecosystem. The impact you will have: Design and manage the Money systems and se

RDQ126R35 About Databricks At Databricks, we empower data teams to solve the world’s toughest challenges—from security threat detection to cancer drug development. Our mission is to build the best data and AI infrastructure platform, enabling our customers to focus on innovation. Our engineering teams push the boundaries of data and AI technology while ensuring our platform operates with the resilience, security, and scale that businesses need to succeed. About the Role We are developing a growing ecosystem of applications and partners on the Databricks Data Intelligence Platform. Our team creates frameworks, tools, and best practices to enable seamless integrations, helping developers and partners build impactful solutions. As a Senior Staff Software Engineer, you will define the vision, architecture, and strategy for this ecosystem. You will play a key role in enabling customers to integrate cutting-edge applications, helping developers thrive on Databricks, and shaping the future of data and AI platforms. Your Impact Define and drive the ecosystem strategy for Databricks, a crucial pillar of our platform growth. Shape how applications and integrations enhance the Databricks experience for developers, partners, and customers. Develop frameworks, APIs, and tools that make it seamless for partners and developers to build, integrate, and scale applications within the Databricks ecosystem. Enable customers to integrate cutting-edge applications and specialized functionalities, helping them drive competitive differentiation and expand their AI and data capabilities. Lead and mentor engineers across teams, providing technical guidance, architectural direction, and career development support. Foster a culture of innovation, best practices, and knowledge sharing. Collaborate cross-functionally with product, engineering, and business development teams to align technical roadmaps with strategic business goals. Engage with open-source communities and advocate for best practi

P-1348 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Our engineering teams build technical products that fulfill real, important needs in the world. We always push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is important to making customers successful on our platform. We develop and operate 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 observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. As a Staff Software Engineer working on the Data Platform team you will help build the Data Intelligence Platform for Databricks that will allow us to automate decision-making across the entire company. You will achieve this in collaboration with Databricks Product Teams, Data Science, Applied AI and many more. You will develop a variety of tools spanning logging, orchestration, data transformation, metric store, governance platforms, data consumption layers etc. You will do this using the latest, bleeding-edge Databricks product and other tools in the data ecosystem - the team also functions as a large, production, in-house customer that dog foods Databricks and guides the future direction of the product. The impact you will have: Design and run the Databricks metrics store that enables all business units and engineering teams to bring their detailed metrics into a common platform for sharing and aggregation, with high quality, introspection ability and query performance. Design and run the cross-c

P-1348 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Our engineering teams build technical products that fulfill real, important needs in the world. We always push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is important to making customers successful on our platform. We develop and operate 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 observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. As a Senior Software Engineer working on the Data Platform team you will help build the Data Intelligence Platform for Databricks that will allow us to automate decision-making across the entire company. You will achieve this in collaboration with Databricks Product Teams, Data Science, Applied AI and many more. You will develop a variety of tools spanning logging, orchestration, data transformation, metric store, governance platforms, data consumption layers etc. You will do this using the latest, bleeding-edge Databricks product and other tools in the data ecosystem - the team also functions as a large, production, in-house customer that dog foods Databricks and guides the future direction of the product. The impact you will have: Design and run the Databricks metrics store that enables all business units and engineering teams to bring their detailed metrics into a common platform for sharing and aggregation, with high quality, introspection ability and query performance. Design and run the cross-

P-940 (Position Location is open to both our Seattle & Bellevue offices.) At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. 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. We develop and operate 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 software engineer with a backend focus, you will work closely with your team and product management to prioritize, design, implement, test, and operate micro-services for the Databricks platform and product. This implies, among others, writing software in Scala/Java, building data pipelines (Apache Spark, Apache Kafka), integrating with third-party applications, and interacting with cloud APIs (AWS, Azure, CloudFormation, Terraform). Below are some example teams you can join: Data Science and Machine Learning Infrastructure: Build services and infrastructure

P-1127 At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Our engineering teams build highly technical products that fulfill real, important needs in the world. We develop and operate 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. The Delta DML team owns the core write-path operations for Delta Lake, the open-source storage layer behind the Databricks Lakehouse. Our mission is to deliver industry-leading performance and a seamless user experience at massive scale, with most data written in Databricks flowing through our platform. We drive performance innovations like Low Shuffle Merge and Deletion Vectors and actively contribute to open source efforts to unify Delta and Iceberg formats. We are seeking a highly skilled and experienced Senior Staff Software Engineer to join our backend team. In this role, you will be instrumental in designing, developing, and maintaining robust backend systems that power Databricks workspaces. You will build the next-generation platform for serving workspace assets, ensuring high QPS, low latency, reliable, and performant systems, proactively addressing the future growth challenges. Additionally, as a senior member of the team, you will provide technical leadership, mentorship, and guidance to junior engineers, contributing to the overall improvement of team coding practices and system designs. The Impact you will have: Solve real business needs at large scale by a

P-1137 Summary At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions. Founded in 2013 by the original creators of Apache Spark, Databricks has grown from a tiny corner office in Berkeley, CA to a global organization with over 1500 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest-growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. 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. Customers trust Databricks with their most valuable data and Trust & Safety has the mission to build the most trusted data analytics and ML platform in the world. Security Engineering is an integral part of Trust & Safety and has a critical role to play in keeping customer data from bad actors. We are looking for senior leaders such as yourselves to create the vision and define the strategy for this space. The impact you will have: Make Databricks safer for our customers by identifying and plugging key gaps in our infrastructure and services Attract top talent from across the industry. Represent the security engineering discipline throughout the organization, having a powerful voice to make us more data-driven Represent Databricks at academic and industry conferences & events What we look for: 5+ years of experience in Data Security or related areas and expertise in two or more of the following--Cryptography, Kubernetes Security, Web Security, Governance,

Staff Software Engineer - Money Team P-940 At Databricks, we are obsessed with Data + AI to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions. Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, CA to a global organization with over 6500 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest-growing SaaS companies in the world. The Money team's mission at Databricks is to maximize the value that our customers derive from their investments in data projects. We accomplish this through innovative commercialization strategies and cutting-edge engineering. Our team ensures timely, accurate, and customizable billing and usage data, alongside budgeting, forecasting, and cost optimization tools. We provide a seamless and consistent billing experience for all our customers, whether they are large enterprises or individual developers, across different pricing plans and cloud providers (AWS, GCP & Azure). As a software engineer on the Money team, you will be closely involved in the entire billing process, including usage ingestion, metering, pricing, credits, promotions, payments, usage reporting, and cost center and budgeting. Your role is crucial in democratizing data by bringing Databricks products to market. By collaborating with marketing, product teams, commercialization experts, data scientists, IT, and customer support, you will standardize billing experiences across major cloud providers, offering our customers a unified "sky computation" experience. This role involves utilizing the latest Databricks products and tools within the ecosystem. The impact you

Company Description: At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform, so our customers can focus on the high value challenges that are central to their own missions. The Mosaic AI organization enables companies to develop AI models and systems using their own data, with technologies ranging from fine-tuning LLMs for enterprise domains, to a platform for building compound AI systems that use retrieval and agents. Mosaic AI is committed to the belief that a company’s AI models are just as valuable as any other core IP, and that high-quality AI models should be available to all. Job description: Most of the world's data+AI problems lie in enterprise domains, behind closed doors. Our research team's goal is to push the frontier of "domain adaptation" - how can we develop LLMs and AI systems that work well for custom domains. To do this we are tackling open research problems on a range of topics, from how to scale/automate eval, fine tune with synthetic data, retrieval augmentation, fast/efficient inference and more. You will work with our research team on projects focused on adapting LLMs and AI systems towards enterprise domains. This may include: Adapting, improving, and evaluating a method from the literature. Designing an entirely new method for domain adaptation. Composing together multiple methods to create new recipes for efficient post-training. Evaluation of LLMs and AI systems. Your qualifications and qualities: Required: Research experience in and proficiency with the fundamentals of deep learning. Pursuing a PhD in computer science or related fields (electrical engineering, neuroscience, physics, math, etc.). Proficient software engineering skills, including with PyTorch. Pay Range Transparency Databricks is committed to fair and equitable compensation prac

P-940 (Position Location is open to both our Seattle & Bellevue offices.) At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. 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. We develop and operate 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 software engineer with a backend focus, you will work closely with your team and product management to prioritize, design, implement, test, and operate micro-services for the Databricks platform and product. This implies, among others, writing software in Scala/Java, building data pipelines (Apache Spark™, Apache Kafka), integrating with third-party applications, and interacting with cloud APIs (AWS, Azure, CloudFormation, Terraform). Below are some example teams you can join: Data Science and Machine Learning Infrastructure: Build services and infrastructu

P-186 At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. 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. We develop and operate 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. Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll-up and drill-down capabilities of traditional SQL query engines. As a software engineer on the Runtime team at Databricks, you will be building the next generation distributed data storage and processing systems that can outperform specialized SQL query engines in relational query performance, yet provide the expressiveness and programming abstractions to support diverse workloads ranging from ETL to data science. Below are some example projects: Apache Spark™ : Develop the de facto open source standard framework for big data. Da

P-186 At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. 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. We develop and operate 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. Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll-up and drill-down capabilities of traditional SQL query engines. As a software engineer on the Runtime team at Databricks, you will be building the next generation distributed data storage and processing systems that can outperform specialized SQL query engines in relational query performance, yet provide the expressiveness and programming abstractions to support diverse workloads ranging from ETL to data science. Below are some example projects: Apache Spark™ : Develop the de facto open source standard framework for big data. Da