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
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P-150 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 at the intersection of machine learning and distributed systems. Our te
P-150 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 at the intersection of machine learning and distributed systems. Our
P-344 At Databricks, our customers challenge us with solving some of the world's toughest data problems. Our customers rely on our Solutions Architect team to understand the technologies that power our platform, the broader cloud and technology ecosystems, and how they can all be brought together to solve these problems. Solutions Architects at Databricks lead the adoption of the Databricks Unified Analytics Platform. As a member of our team, you will sharpen your skills on open-source projects such as Apache Spark™, MLflow, and Delta Lake to advocate the Lakehouse paradigm on public cloud providers. You will gain expertise in cloud platforms, data engineering, data analytics, data science, and machine learning. In this customer-facing role, you will identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through implementations to deliver strategic business value. You will partner with the sales team to build relationships with our customers and establish yourself as a trusted advisor. Databricks' culture thrives on collaboration and teamwork, and you will contribute your knowledge to our teams by participating in our subject matter expert groups. In this role, you will report to the Solutions Architect Leader supporting the specific business segment. If you are a technologist interested in Data and AI, and enjoy prototyping solutions for customers, this role is for you. The impact you will have: Provide technical leadership for customers to evaluate and adopt Data and AI solutions from Databricks Consult on big data architecture, implement proof of concepts for strategic customer projects, data science and machine learning projects, and validate integrations with cloud services and other 3rd party applications Build and present reference architectures, technical guides, and demo applications for customers Provide escalated support for critical customer operational issues Become an expert in, and evangelize Dat
P-345 At Databricks, our customers challenge us with solving some of the world's toughest data problems. Our customers rely on our Solutions Architect team to understand the technologies that power our platform, the broader cloud and technology ecosystems, and how they can all be brought together to solve these problems. Solutions Architects at Databricks lead the adoption of the Databricks Unified Analytics Platform. As a member of our team, you will sharpen your skills on open-source projects such as Apache Spark™, MLflow, and Delta Lake to advocate the Lakehouse paradigm on public cloud providers. You will gain expertise in cloud platforms, data engineering, data analytics, data science, and machine learning. In this customer-facing role, you will identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through implementations to deliver strategic business value. You will build relationships with our customers and establish yourself as a trusted advisor. Databricks' culture thrives on collaboration and teamwork, and you will contribute your knowledge to our teams by participating in our subject matter expert groups. In this role, you will report to the Solutions Architect Leader supporting the specific business segment. If you are a technologist interested in Data and AI, and enjoy prototyping solutions for customers, this role is for you. The impact you will have: Provide technical leadership for customers to evaluate and adopt Data and AI solutions from Databricks Consult on big data architecture, implement proof of concepts for strategic customer projects, data science and machine learning projects, and validate integrations with cloud services and other 3rd party applications Build and present reference architectures, technical guides, and demo applications for customers Provide escalated support for critical customer operational issues Become an expert in, and evangelize Databricks driven open-source proj
P-273 While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered. #LI-REMOTE As a Solutions Architect on the Digital Natives team, you will shape the future of the big data landscape by working with the most sophisticated data engineering and data science teams in the world. Reporting to the Field Engineering Manager, you will collaborate with customers, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide customers through the competitive landscape, best practices, and implementation; and develop technical champions along the way. The impact you will have: You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems. Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications Collaborate with your fellow Solutions Architects, using your skills to support each other and our users Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community. What we look for: 5+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role Experience building distributed data systems Comfortable programming in, and debugging, Python and SQL Have built solutions with public cloud providers such as AWS, Azure, or GCP Expertise in one of the following: Data Engineering technologies ( Ex: Spark, Hadoop, Kafka ) Data Science and Machine Learning technologies ( Ex: pandas, scikit-learn, pytorch, Tensorflow ) Avai
About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more. You'll be deeply embedded where people get things done. You'll ship agentic capabilities on an open, extensible stack, with
Sigmoid Analytics is a leading Data solutions company backed by Sequoia Capital. We offer best in- end-to-end data value chain spanning across Data Science, Data Engineering and Data Ops. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modelled around expertise and mutual respect with a team first mindset. You’ll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire. Offices : New York | Dallas | San Francisco | Lima | Bengaluru The below role is for our Bengaluru office. About the Role : You will work on a broad range of cutting-edge data science and machine learning problems across a variety of industries. You will be engaging with clients to understand their business context. If you are passionate to work on complex unstructured business problems that can be solved using data science and machine learning, we would like to talk to you. Role: ALDS Mandate Skills & Competencies: Experience in Programming (Python, R, SQL, NoSQL, Spark) with ML tools & Cloud Technology (AWS, Azure, GCP) Experience in Python libraries such as NumPy, pandas, scikit-learn, tensor-flow, scapy, scrapy, BERT etc. Good understanding in statistics, and ability to design statistical hypothesis testing to aid formal decision making. Develops predictive models using Machine Learning algorithms (SVM, Random Forest, Neural Network, Decision Tree, Logistic Regression, K-mean Clustering, linear regression, PCA etc.) Engaging with clients, understanding complex problem statements, and offering solutions in the domains of Retail, Pharma, Banking, Insurance, etc. Contribute to internal product development initiatives related to data science. Develop data science roadmap, and guide data scientist to meet their deliverables. Handling end-to-end client AI & analytics programs. Your role will be a combination of hands-on contribution, technical team management, and c
A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role We’re looking for Site Reliability Engineers who can help us build, operate, and maintain high-performance, scalable, and reliable services for our production infrastructure, across both cloud & on-prem environments. Site Reliability Engineers combine engineering experience and an innate drive to improve existing systems and processes, with the creativity to develop novel solutions to evolving challenges. Our team strives to automate processes wherever possible, using whichever tools are best for the job. You’ll be the experts for the environments that you operate infrastructure in, helping partner teams build & configure their software to operate reliably within. We strongly believe in engineering teams being responsible for the operations of their services in production. In this role, you’ll work closely with engineers to advocate and participate in sensible, scalable, systems design and share responsibility with them in diagnosing, resolving, and preventing production issues. Core Responsibilities Maintaining availability of cloud & physical Linux servers that power the Palantir platform in air-gapped production environments Design, deploy, and operate infrastructure to support customer & product requirements via modern orchestration & monitoring platforms. Collaborate closely with product teams on requirements & SLOs for deploying software into air-gapped environments. Identifying, troubleshooting, and solving network & systems issues Scripting to automate away routine operational tasks Provide technical troubleshooting support for production issues, ensuring timely resolution and m
Présentation du poste : Au sein de l’équipe Data Analytics d'Artefact, vous rejoignez un pôle clé couvrant le dashboarding, l'analytics engineering, la mesure marketing et le low-code data science. En tant que Manager, vous intervenez auprès de grands comptes pour piloter des projets d'analyse de données stratégiques, définir des architectures de mesure robustes et faire croître nos expertises. Ce qu’on attend de vous : En tant que Manager, vous garantissez l'excellence opérationnelle et la qualité des livrables sur des projets pluridisciplinaires (data analysts, consultants, software engineers, data scientists). Vous jouez un rôle central dans le cadrage d'offres avancées, la conduite des avant-ventes (pitches) et l'encadrement des équipes, tout en faisant rayonner l'expertise Data Analytics d'Artefact sur le marché. Vos missions : Piloter la réalisation de projets Data Marketing & Analytics complexes : déploiement d'outils de mesure (online/offline), projets de modélisation avancée, CDP, MMM et Clean Rooms. Encadrer des équipes pluridisciplinaires et veiller au respect des plus hauts standards de qualité, de rigueur et d'automatisation (scripting, reporting, développement d'outils). Définir la stratégie et la feuille de route de l'offre Data Analytics : formaliser les meilleures pratiques, développer des méthodologies de mesure innovantes et animer la communauté d'experts. Porter la dimension Data Analytics lors des phases d'avant-vente (pitches) et auprès des décideurs clients pour positionner Artefact comme un partenaire stratégique sur le long terme. Développer l'expertise technique et analytique interne : tester de nouvelles approches (ex. GenAI appliquée à l'analytics, MCP pour la BI, interfaces conversationnelles), créer des accélérateurs et former les équipes. Mentorer les collaborateurs, assurer le suivi des compétences et garantir un environnement de travail collaboratif et exigeant. Profil recherché : Expérience & Leadership : 5 ans ou plus d'exp
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Snowflake is building the most powerful AI Data Cloud in the world — and Canada is a critical part of that mission. Our AI/ML engineering teams are delivering the intelligence layer that powers Cortex AI, large language model inference, AI functions, intelligent search, and the next generation of AI-powered experiences on the Snowflake platform. We're looking for a Software Engineer — AI to join our growing Toronto engineering team. You'll design, build, and ship AI-powered systems and services that are used by thousands of organizations worldwide. If you're passionate about building production AI infrastructure at scale and want to work alongside world-class engineers on problems that matter, this is the role. AS A SOFTWARE ENGINEER — AI, YOU WILL: Design, develop, and ship AI-powered features and services — working across model inference, AI functions, retrieval systems, and intelligent application experiences on the Snowflake platform Build production-quality infrastructure for AI workloads — including model serving, embedding pipelines, retrieval-augmented generation (RAG), and AI-driven automation Write clean, performant, and well-tested code in languages like Python, Java, C++, or Go — contributing to systems that operate at enterprise scale across Snowflake's multi-c
Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy. As a Principal Engineer / architect you will be responsible for creating a technical strategy and coordinating the designs for meeting the needs of Toast’s largest restaurant brands. You will partner with Product Managers to develop the technology roadmap that enables enterprise customers to leverage the power of Toast. You will also work closely with technical leaders and implementation teams across the organization to deliver robust, scalable solutions with integrations to customers’ external systems. While the role is primarily internally-facing, it requires infrequent interactions with enterprise customers, listening to their requirements and providing expert guidance as they deploy Toast. If you’re a technical leader or a solutions architect, experienced with enterprise SaaS, passionate about customer value, and a great collaborator, read on! A day in the life (Responsibilities) Lead the evolution of Toast’s backend architecture , frameworks, and data models with a strong focus on delivery efficiency, system scalability, and resilience. Design and build the next generation of accounting and financial systems using Java, Kotlin, DynamoDB, Pulsar, GraphQL, Big Data tools , and more. Define and implement scalable engineering practices , delivery frameworks, and coding standards that raise the technical bar across the org. Collaborate cross-functionally with Product, UX, QA , and multiple engineering teams to deliver robust, customer-facing solutions. Build and maintain strong partnerships across business units, aligning technology strategies with key company objectives. Champion data-driven decision making by developing strategies and prioritizing initiatives with high impact on user and business outcomes. Mentor and grow engineers across levels, promoting a culture of inclu
We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary As a Sr. Software Development Engineer, you will partner with our stellar engineering, product, and design teams in a fast-paced, agile environment to transform ideas into a reality. Utilizing modern methodologies and open source tools, you will be empowered to push the boundaries of development as we seek to deliver applications that will directly and immediately impact the experience of our teams and our patients. Required Qualifications Technical Design Experience 6+ years of experience building large consumer-facing products using Ruby or Java/Kotlin. Experience working in a distributed, cloud-based environment either in Azure/AWS using Docker/Kubernetes. Experience using AI-assisted development tools (e.g., GitHub Copilot, Cursor, Claude) to enhance productivity and code quality. Experience with unit & integration testing. Experience in building cloud native scalable Microservices Experience working with MongoDb or PostgreSQL Experience working in an Agile/Devops environment US work authorization Preferred Qualifications Familiarity with our tech stack: Ruby, GraphQL, AWS DevOps, Kubernetes, PostgreSQL, MongoDB. Ex
Strength in Trust OneTrust’s mission is to enable innovation through the responsible use of data and AI. We believe that ensuring data is trusted shouldn’t slow teams down—it should accelerate what’s possible. This led us to develop the first technology platform for responsible data use in 2016. Today, with AI representing the latest and most impactful expansion of data yet, OneTrust is once again redefining what responsible innovation looks like. OneTrust, the AI‑Ready Governance Platform™, unifies regulatory intelligence, automation, and connected governance workflows so businesses can continue to move at the speed of AI while ensuring good governance to prevent data misuse at scale. Trusted by thousands of organizations worldwide, OneTrust is shaping the future where trusted data becomes a transformative force for business and society. Strength in Trust OneTrust’s mission is to enable innovation through the responsible use of data and AI. We believe that ensuring data is trusted shouldn’t slow teams down - it should accelerate what’s possible. This led us to develop the first technology platform for responsible data use in 2016. Today, with AI representing the latest and most impactful expansion of data yet, OneTrust is once again redefining what responsible innovation looks like. OneTrust, the AI ‑ Ready Governance Platform™, unifies regulatory intelligence, automation, and connected governance workflows so businesses can continue to move at the speed of AI while ensuring good governance to prevent data misuse at scale. Trusted by thousands of organizations worldwide, OneTrust is shaping the future where trusted data becomes a transformative force for business and society. The Challenge OneTrust is seeking a Staff Technical Specialist Engineer to join our R&D Customer Engineering organization and help drive innovation across our AI Governance portfolio. This role combines the technical depth of a software engineer wit
Principal Data Privacy Architect Description - Job Summary - Role Purpose • Lead and oversee complex, cross-functional privacy and data protection programs from strategy through implementation, ensuring alignment across business, technical, legal, and compliance stakeholders. • This role will design and implement scalable, AI-ready data privacy architecture across enterprise data environments, applications, and AI-enabled workflows. • The Principal Data Privacy Architect will serve as a hands-on subject matter expert responsible for embedding privacy-by-design, consent enforcement, data sovereignty, data loss prevention, and compliance controls into large, complex global data environments. • The architect will partner closely with Data Engineering, Cybersecurity, Legal, Privacy, AI Governance, Product, and Enterprise Architecture teams to ensure customer, employee, partner, and sensitive enterprise data is accessed, processed, shared, retained, and protected in a compliant, secure, and trustworthy manner. - Why This Role Matters • Architect for Trust & Scale: Build reusable privacy architecture patterns that enable secure, compliant, and scalable data usage across platforms, products, and regions. • Enable Responsible AI: Design privacy guardrails for AI agents, generative AI, RAG pipelines, model inputs and outputs, embeddings, vector stores, and automated data workflows. • Reduce Risk While Enabling Innovation: Translate privacy, consent, regulatory, and data sovereignty obligations into practical engineering controls that accelerate business outcomes. Responsibilities - Think Customer First • Embed customer trust, transparency, and privacy-by-design principles into enterprise data platforms and customer-facing applications. • Design consent-aware data access and usage p
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