Data Analytics Engineer Jobs

Drata is building the trust layer between great companies - automating compliance, managing risk, and helping organizations prove trust continuously as they scale. We're Dratanauts: a global crew of 600+ professionals united by a culture that rewards integrity, ownership, and raising the bar, no matter where in the world we're working from. Why Join the Drata Team? At Drata, you're not maintaining legacy compliance software - you're building the agentic AI platform defining what trust looks like for the next generation of companies. Here's what makes the work itself worth showing up for: Problems without a playbook: You'll work at the edge of AI and security, building agentic governance, continuous compliance, and real-time trust verification to solve problems that don't have an established answer yet. You're writing it as you go. Real ownership, not just process: Our values center on owning outcomes and raising the bar, not checking boxes. You're expected to have opinions and back them. A seat at the table: Your perspective is unique and valued. Open debate and diverse viewpoints are built into how decisions actually get made here, at every level. Growth at rocketship speed: Drata is scaling fast, which means scope grows fast too. High performers get more ownership, visibility, and experience. A crew, not just coworkers: Dratanauts consistently describe a "come as you are" culture with sharp, curious people—the kind of team that makes hard problems genuinely fun to solve. See what they say here and follow us on LinkedIn for company news, employee stories, and career updates. Job Summary: Drata's AI Platform team builds the production infrastructure that powers AI features across our compliance platform — from MCP servers that make Drata's data available to AI agents, to LLM workflow orchestration that automates SOC 2, TPRM, and policy analysis. You'll own the systems that sit between our AI models and our customers: tool definitions that agents actually understand,

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? We are on a mission to build machines that understand the world and make them safely accessible to all. Data quality is foundational to this process. Machines (or Large Language Models, to be exact) learn in similar ways to humans, by way of feedback. By labelling, ranking, auditing, and correcting model output, you will improve Large Language Models' performance for iterations to come, thus having a lasting impact on Cohere's technology. We are hiring Generalist professionals with broad backgrounds that span multiple consumer-facing or personal domains. This is a judgment-driven role, not passive data entry. You will review, assess, and provide structured feedback across a broad and evolving range of tasks, evaluating, stress-testing, and improving our models on English-language data spanning multiple modalities (text, image, and structured formats such as JSON, CSV/TSV, and Markdown). This is a great opportunity for professionals with strong analytical skills to contribute to high-impact annotation projects. Please Note: This is a part-time independent contractor position available within Canada only. We seek ca

Join the MongoDB Server Query Execution team, and help us build a world-class distributed open-source database. Our team plays a crucial role in the performance and efficiency of MongoDB's data processing. We are responsible for building and improving the core execution engine that powers all queries, taking a logical query plan produced by the optimizer and turning it into reality. This includes developing the physical operators for data retrieval and manipulation, improving the runtime for complex analytical and transactional workloads, and owning critical components such as our new execution engine. In addition to the core server, we support the query execution needs of other major products like Atlas Streams, Atlas Search and Vector Search, and mongosync, making our work vital to the entire MongoDB ecosystem. You will be joining a globally distributed team with a significant presence in both North America and Europe. While this role is based in the NAMER region, you will regularly collaborate closely with colleagues across different time zones. We support both office-based work in our North America hubs like New York, as well as remote work. We have tons of interesting problems to solve with a direct impact on users for transactional, time-series, and analytical workloads. To meet the ever-increasing data demands of modern applications, we are actively evolving our query system; this includes strategically re-architecting and improving key components of our query execution engine. We need your help to design and build the core of a distributed, flexible schema document database. This role can be based out of one of our North America offices, such as NYC or Palo Alto, or remotely across North America. Candidate Profile 10+ years of hands-on, professional experience in query engine development or database internals Experience with building production-level code with a large user base, robust design structure and rigorous code quality Degree in Computer Science or

WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com. Why we're hiring: Detection Engineering is responsible for designing, developing, and maintaining high-fidelity detection logic across enterprise security platforms. This role focuses on proactive threat detection, automation-first practices, and continuous improvement of detection coverage and accuracy, supporting the WPP SOC transformation into an Autonomic Security Operations model. What you'll be doing: Develop, test, and maintain detection rules and logic across SIEM, EDR, NDR, and cloud-native platforms. Regularly review and enhance detection logic to improve accuracy, reduce noise, and align with evolving threats. Work with wider WPP engineering teams to ensure high-quality, normalized telemetry for effective detection. Automate detection rule deployment, QA, and version control using scripting and CI/CD pipelines. Root Cause Analysis (RCA) Conduct RCA on missed detections, delayed responses, and high-severity incidents. Identify technical and process-level causes of detection failures or inefficiencies. Drive corrective actions based on RCA outcomes (e.g., rule improvements,

Leidos has an exciting opportunity for Cyber Security Engineer—Technical Lead in our Intel Security Sector's Analysis Solutions Business Area . Our talented team is at the forefront in Security Engineering, Computer Network Operations (CNO), Mission Software, Analytical Methods and Modeling, Signals Intelligence (SIGINT), and Cryptographic Key Management. At Leidos , we offer competitive benefits , including Paid Time Off, 11 paid Holidays, 401K with a 6% company match and immediate vesting, Flexible Schedules, Discounted Stock Purchase Plans, Technical Upskilling, Education and Training Support, Parental Paid Leave, and much more. Join us and make a difference in National Security! Job Summary This role is responsible for protecting the customer’s information systems and networks from potential cyber-attacks. The Cyber Security Engineer– Technical Lead will serve in a hands-on “player-coach" capacity, dedicating approximately 75% of time to direct technical engineering, troubleshooting, and implementation work, while providing technical leadership and coordination across the security team. The candidate must display an excellent understanding of technology and utilization of Firewalls (Security Groups), VPNs, Data Loss Prevention (DPS), IDS/IPS, Web-Proxy, Security tools, and Security Audits. Candidate will work directly with Team leads, developers, operations personnel, and other Technical Leads throughout a DevSecOps life cycle both on policy and technical implementation of technologies. This is not a supervisory management role. Success in this position is measured by individual technical contribution and resolution of complex security issues, in addition to technical leadership impact. Primary Responsibilities: Plan, implement, manage, monitor, and upgrade security controls and tools used to protect enterprise systems and networks, while identifying opportunitie

About Graphcore Graphcore is a global leader in artificial intelligence computing systems. We design advanced semiconductors, software, and data center systems that provide the specialized processing power needed to advance AI while improving the efficiency required for broad adoption. As part of SoftBank Group, Graphcore belongs to a family of companies developing transformative technologies. Our U.S. engineering teams contribute to the hardware and software platforms that support the next generation of AI systems. The Opportunity We are looking for a recent graduate or early-career engineer to join the BMC Engineering team as a Graduate Firmware Engineer. You will develop low-level and embedded firmware that supports the operation, control, monitoring, and validation of advanced compute systems. You will work with experienced firmware, hardware, systems, and software engineers throughout the development lifecycle. The role combines hands-on implementation with automated testing, lab-based debugging, hardware bring-up, and analysis of interactions between firmware and the underlying platform. Start: September, 2027 Location: Austin, Texas, USA What You Will Do Design, implement, test, and maintain system and embedded firmware in C, C++, or Python. Take ownership of defined firmware features and deliver them from requirements and design through implementation, validation, and documentation. Develop and debug firmware in a Linux-based engineering environment using appropriate diagnostic tools and techniques. Create automated tests and scripts that improve firmware validation, test coverage, and engineering efficiency. Contribute to continuous integration and delivery workflows for firmware development and testing. Plan and conduct engineering experiments, analyze test data, and communicate findings clearly. Support lab setup, system configuration, hardware bring-up, and firmware validation on development platforms. Investigate firmware behavior and hardware-software

Job Details: Job Description: Intel Foundry Automation - Back End Automation Group is seeking a talented student to support our Automation Integrators in advancing manufacturing automation systems. Key Responsibilities: • Assist Automation Integrators with troubleshooting, system upgrades, user training, and root cause analysis to improve efficiency and reduce waste. • Enable Automation Integrators in designing, developing, testing, and debugging software for factory operations, wafer processing, and packaging across multiple software layers. • Support client-based Station Controller systems through validation, troubleshooting, and quality control. Collaborate with global cross-functional teams to drive automation projects and integrate machine learning and AI solutions as needed. Qualifications: Candidates must be currently pursuing a bachelor's degree in computer science, Data Science, Computer Engineering, or a related discipline. They should possess strong analytical, problem-solving, and communication skills, along with hands-on programming experience in languages such as Python, C, and C#. Knowledge of Agile software development methodologies and experience with manufacturing systems are highly desirable. Job Type: Student / Intern Shift: Shift 1 (Malaysia) Primary Location: Malaysia, Penang Additional Locations: Malaysia, Kulim Posti

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Responsibilities Analyze inline/param/probe/DOE data to identify yield detractors and drive continuous improvement. Apply semiconductor device physics, process knowledge, and statistical tools to troubleshoot yield issues. Collaborate with module engineering teams to diagnose process/tool‑related yield variation and ensure timely resolution. Lead or participate in cross‑functional task forces to solve complex yield, defect, or process integration challenges. Perform root‑cause analysis using FMEA, 8D, SPC, and other structured methodologies. Publish clear Pareto analyses and maintain dashboards for assigned product lines. Support new technology transfer, process baseline setup, and qualification activities. Partner with equipment engineering, shift engineering, and quality teams to address long‑term defect or excursion issues. Conduct material, process, and equipment evaluations and recommend optimization strategies. Ensure product performance meets design and reliability requirements and propose corrective actions when gaps exist. Leverage AI-Enabled and AI-Assisted solutions, including Copilot, YMS Genie, Agentic AI, AI Agents, and Large Language Models (LLMs), to accelerate yield analysis, automate engineering workflows, summarize insights, and enhance diagnostic efficiency. <spa

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. At Micron, we are transforming how the world uses information to enrich life. The High Bandwidth Memory (HBM) Design team develops industry-leading memory solutions that enable advances in Artificial Intelligence, high-performance computing, graphics, and data-center applications. Our engineers collaborate across global teams to deliver innovative memory architectures and semiconductor technologies that power next-generation computing systems. As an HBM Design Engineer Intern, you will work alongside experienced memory engineers and gain hands-on experience in semiconductor design, simulation, verification, and analysis. This internship provides exposure to industry-standard design methodologies, EDA tools, and cross-functional collaboration throughout the product development lifecycle. You will also have opportunities to apply AI-Assisted and AI-Enabled workflows to improve engineering productivity, debug efficiency, and design quality. Responsibilities Assist with the design, simulation, analysis, and verification of HBM memory and logic circuits using industry-standard semiconductor design tools. Support RTL development, circuit implementation, timing analysis, power analysis, and functional validation activities. Develop scripts, automation solutions, and AI-Assisted workflows to improve design productivity, debug efficiency, and design-flow quality. Collaborate with Design, Verification, Physical Design, CAD, and Product Engineering teams on technical reviews, debug activities, and project deliv

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. At Micron, we are transforming how the world uses information to enrich life. The High Bandwidth Memory (HBM) Design team develops industry-leading memory solutions that enable advances in Artificial Intelligence, high-performance computing, graphics, and data-center applications. Our engineers collaborate across global teams to deliver innovative memory architectures and semiconductor technologies that power next-generation computing systems. As an HBM Design Engineer Intern, you will work alongside experienced memory engineers and gain hands-on experience in semiconductor design, simulation, verification, and analysis. This internship provides exposure to industry-standard design methodologies, EDA tools, and cross-functional collaboration throughout the product development lifecycle. You will also have opportunities to apply AI-Assisted and AI-Enabled workflows to improve engineering productivity, debug efficiency, and design quality. Responsibilities Assist with the design, simulation, analysis, and verification of HBM memory and logic circuits using industry-standard semiconductor design tools. Support RTL development, circuit implementation, timing analysis, power analysis, and functional validation activities. Develop scripts, automation solutions, and AI-Assisted workflows to improve design productivity, debug efficiency, and design-flow quality. Collaborate with Design, Verification, Physical Design, CAD, and Product Engineering teams on technical reviews, debug activities, and project deliv

We build and operate the compute infrastructure our researchers run on, supporting large-scale processing of historical market data and model training on our own hardware across multiple data centers. Our environment includes bare-metal Linux, virtualization, storage, and GPU clusters, where performance, reliability, and predictable system behavior are critical. Our Infrastructure team covers monitoring and automation, distributed storage, hardware and OS provisioning, GPU clusters and workload scheduling, high-speed networking, L2/L3 Linux support, and security engineering. Engineers here own their tasks end to end, so there's room to go deeper in your area and pick up the parts you haven't touched yet. We’re looking for a Linux Infrastructure Engineer who can work hands-on with server and cluster environments, from deployment and configuration to performance tuning, troubleshooting, and ongoing improvement What You’ll Be Doing: Deploying, configuring, and maintaining Linux-based bare-metal servers across our data centers Building and operating clustered environments, including virtualization, storage, GPU compute, and database clusters Troubleshooting complex Linux, hardware, networking, and cluster-level issues Performance tuning for throughput, latency, stability, and resource utilization Monitoring infrastructure health and performance, identifying bottlenecks, and preventing recurring issues Supporting the full server lifecycle: provisioning, setup, upgrades, and maintenance Improving reliability and predictability during failures, maintenance, and scaling Automating provisioning, configuration, and operational tasks, primarily using Ansible and scripting What We Look For In You: Strong hands-on Linux administration and troubleshooting experience Production experience with on-premise, bare-metal infrastructure Good understanding of Linux performance and bottleneck analysis Experience with: infrastructure monitoring and troubleshooting production issues,

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE As an Escalation Engineer on our FlashBlade team, you will serve as the premier technical authority driving customer trust and operational stability across complex, enterprise-scale storage environments . You will collaborate closely with front-line Support, Engineering, and product leaders to rapidly resolve high-impact technical challenges and transform complex system failures into long-term product reliability. By bridging real-world customer insights with engineering solutions, you will elevate team performance and ensure our enterprise customers achieve flawless platform availability. WHAT YOU'LL DO Drive High-Stakes Escalation Resolution: Take end-to-end ownership of critical, multi-platform system issues—evaluating hardware, software, networking, and environmental factors—to rapidly restore service, perform root-cause analysis, and protect customer business continuity. Elevate Engineering Talent & Knowledge: Mentor and coach support team members through joint case triage, structured technical trainings, and internal documentation, accelerating technical capabilities and resolution velocity across the organization. Bridge Product Engineering & Customer Insights: Partner directly with Product Engineering to relay real-world system behavior, ensuring critical customer feedback, feature enhancements, and bug fixes trickle back into core product design. Lead Strategic Customer Communications: Facilitate

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE As an Escalation Engineer on our FlashBlade team, you will serve as the premier technical authority driving customer trust and operational stability across complex, enterprise-scale storage environments . You will collaborate closely with front-line Support, Engineering, and product leaders to rapidly resolve high-impact technical challenges and transform complex system failures into long-term product reliability. By bridging real-world customer insights with engineering solutions, you will elevate team performance and ensure our enterprise customers achieve flawless platform availability. WHAT YOU'LL DO Drive High-Stakes Escalation Resolution: Take end-to-end ownership of critical, multi-platform system issues—evaluating hardware, software, networking, and environmental factors—to rapidly restore service, perform root-cause analysis, and protect customer business continuity. Elevate Engineering Talent & Knowledge: Mentor and coach support team members through joint case triage, structured technical trainings, and internal documentation, accelerating technical capabilities and resolution velocity across the organization. Bridge Product Engineering & Customer Insights: Partner directly with Product Engineering to relay real-world system behavior, ensuring critical customer feedback, feature enhancements, and bug fixes trickle back into core product design. Lead Strategic Customer Communications: Facilitate

Role Purpose We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on ex

Machine Learning Engineer We’re looking for a Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: Multiple years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: