Senior Data Engineer Jobs

SPECIFIC JOB RESPONSIBILITIES Defensive Operations (SecOps): Design and automate the Security Incident Response (SIR) and Vulnerability Response (VR) lifecycles. Build playbooks in Flow Designer to automate threat containment and remediation. Offensive Operations: Develop custom scoped applications to track penetration testing results, manage red-team engagement lifecycles, and automate the ingestion of reconnaissance data. Compliance & GRC: Configure and customize Integrated Risk Management (IRM) modules to map technical controls to frameworks like SOC2, ISO 27001, HIPAA, and FedRAMP. Integrations & Orchestration: Build robust, secure integrations (REST/SOAP, IntegrationHub , MID Servers) with our XDR, SIEM (Splunk/Sentinel), and cloud-native services (AWS/Azure/GCP). Multi-Tenancy & MSSP Architecture: Architect a scalable, multi-tenant environment that ensures strict data isolation between clients while allowing for unified " ClickOps " and Terraform-driven automation. AI & Innovation: Explore and implement Now Assist (GenAI) and AI-heavy workflows to automate security reporting and incident summarization. Defensive Operations (SecOps): Design and automate the Security Incident Response (SIR) and Vulnerability Response (VR) lifecycles. Build playbooks in Flow Designer to automate threat containment and remediation. Offensive Operations: Develop custom scoped applications to track penetration testing results, manage red-team engagement lifecycles, and automate the ingestion of reconnaissance data. Compliance & GRC: Configure and customize Integrated Risk Management (IRM) modules to map technical controls to frameworks like SOC2, ISO 27001, HIPAA, and FedRAMP. Integrations & Orchestration: Build robust, secure integrations (REST/SOAP, IntegrationHub , MID Servers) with our XDR, SIEM (Splunk/Sentinel), and cloud-native services (AWS/Azure/GCP)

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. About the team + role We are building an elite team, applying frontier technologies to the world's biggest financial problems. We're looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn't a place for complacency, it's where ambitious people do the best work of their careers. We're a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. The Developer Infrastructure org is the engine behind Robinhood's entire engineering organization — a collection of tightly integrated teams whose collective mission is to make every engineer at Robinhood faster, more reliable, and exponentially more productive. The org spans four major teams: DevX (Developer Experience), TestX (Test Infrastructure), Backend Platform, and Mobile Platform. DevX owns Robinhood's monorepo and Bazel-based build infrastructure — the critical layer between a developer writing code and that code being ready to ship — along with the company's full CI/CD pipeline and remote build execution cluster. TestX owns the infrastructure behind Robinhood's entire test experience: the integration test environments, and personal development environments that serve as miniature simulations of the full Robinhood system, giving engineers a safe, isolated space to test their code end-to-end before it ever touches production. Backend Platform and Mobile Platform own the core language runtimes, libraries, IDEs, and developer toolchains across Python, Go, TypeScript, Swift, and Android. Together, these teams share a single north star: leveraging AI and agentic systems

PagerDuty (NYSE:PD) is a leader in Digital Operations Management. In an always-on world, organizations of all sizes trust PagerDuty to help them deliver a perfect digital experience to their customers, every time. Teams use PagerDuty to identify issues and opportunities in real time and bring together the right people to fix problems faster and prevent them in the future. Over 13,000 organizations (including 60 of Fortune 100) rely on PagerDuty to succeed with Digital Transformation, Cloud Migration, and DevOps Modernization. Notable customers include GE, Cisco, Genentech, Electronic Arts, Cox Automotive, Netflix, Shopify, Zoom, DoorDash, Lululemon and more. We are expanding rapidly as a platform for Digital Operations Management using AI/ML and Automation and growing our adoption by Development, IT, Customer Service, Security, and other teams across the organization. About the role PagerDuty’s Operations Cloud runs on a platform that ingests billions of signals and turns them into real-time action for thousands of customers. We’re looking for an early-career AI/ML Engineer who is excited to grow at the intersection of two disciplines: large-scale distributed systems and machine learning. In this role you will help build and ship AI systems that run in production at PagerDuty’s scale — powering Incident Management AI Agents, event intelligence, and the LLM-powered capabilities embedded across our platform. You’ll work alongside senior engineers on real production problems, learning how AI features go from a prototype to something that serves reliably at scale. We are looking for a candidate who is genuinely excited about building with modern AI — LLMs, agents, and retrieval — eager to learn how resilient, high-throughput systems are built, and motivated to grow into an engineer who is strong in both. What you’ll do Contribute to AI-powered features — LLM agents, retrieval, and event intelligence — that operate on high-volume, real-time data, with support and guidanc

We are a global team of innovators and pioneers dedicated to shaping the future of observability. At New Relic, we build an intelligent platform that empowers companies to thrive in an AI-first world by giving them unparalleled insight into their complex systems. As we continue to expand our global footprint, we're looking for passionate people to join our mission. If you're ready to help the world's best companies optimize their digital applications, we invite you to explore a career with us! Your opportunity At New Relic, we provide our customers real-time insights, so they can innovate faster. Our software delivers insightful observability tools across different technologies and distributed systems, enabling software engineering teams to quickly identify, understand and tackle issues, analyze performance and get the most of their software and infrastructure. The Infrastructure product organization develops New Relic infrastructure instrumentation agents, next generation data processing and management services, vulnerability management, and security testing capabilities for on-prem and cloud customers. We work with data at a scale using a diverse tech stack (Go, Java, JavaScript, React GraphQL, Kubernetes, many public cloud web services, and more). As a senior backend engineer, you will help us build and extend next generation solutions such as a control plane for customers to manage their data pipelines at scale. New Relic is looking for engineers who are interested in building a brand-new observability experience. This high-impact engineering position is a phenomenal opportunity to own and build a set of next generation services and capabilities for the company. We are searching for a motivated engineer who is ready for a career-defining role in their next opportunity. We look forward to talking with you! What you'll do ● Design, Build, maintain, and scale back-end services and their support tools. ● Participate in architectural definitions with a high degr

The team + the role Pendo's Data & GTM Intelligence org exists to make the revenue organization faster, smarter, and more effective. We sit at the intersection of data, AI, and GTM execution. We hold ourselves accountable to whether the teams we support are getting measurable, lasting value from our work. This role owns the operational foundation for Pendo's Customer Engineering organization: process design, planning cycles, and strategic partnership with CE leadership. You stay close to the business - deeply embedded in the CE org, with a point of view on where process, data, or AI could unlock better outcomes. You also serve as the CE pod lead, the coordination point for Applied AI, Business Systems, and Data work that touches your function. You operate with significant autonomy. You identify what is broken, design the solution, and bring stakeholders along. The best person for this role has strong customer success and sales engineering domain knowledge, sharp analytical instincts, and genuine enthusiasm for rebuilding operations around AI. What this looks like day-to-day Own core CE operational work: book-of-business design, territory assignments, capacity planning, and quota framework support. Design, document, and improve CE processes end-to-end including onboarding handoff workflows, renewal and expansion pipeline governance, risk escalation protocols, and success plan hygiene. Partner with Analytics to translate data into clear, actionable recommendations for CE leadership. Serve as the coordination point between CE and the Business Operations functions (Applied AI, Data, Systems). Understand where CE teams are running into friction - where they are losing time, where the data is wrong, where process gaps are costing renewals. Identify where manual work is slowing CEs down and bring a clear point of view to Applied AI on where automation or AI would have the most impact. Maintain Salesforce data standards for CE: define what good looks l

Shape the Future with Dun & Bradstreet At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. Since 1841, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers. The Role: We are looking for a highly skilled AI Tool / Agent Testing Engineer to evaluate, validate, and ensure the reliability of AI agents, AI automation tools, and agentic workflows used across our analytics platform. This role blends test engineering, GenAI understanding, Python/PySpark proficiency, and agent development lifecycle knowledge. You will work closely with Data Science, AI Engineering, and Platform teams to ensure that AI agents behave predictably, safely, and in alignment with business and compliance requirements.

The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It’s why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it’s why our business strategy centers on making journalism so good that it’s worth paying for. About the Role New York Times Wirecutter team is looking for a Senior Manager, Audience & Product Analytics to power our growth strategy. Your core mandate will be to build an understanding of our audience— who they are, how they engage with content and product features, and what brings them back. You will lead a team of analysts responsible for understanding audience trends, driving product improvement, and optimizing user engagement. You will provide leadership and data-driven insights, working with audience, product, and engineering leads to establish goals, design experiments, and uncover new opportunities. You will report to the Executive Director of Data Analytics and Insights, Wirecutter. This opportunity is flexible to in office or remote work. Responsibilities You will manage a team of three direct reports—promoting a culture of curiosity and excellence while setting clear deliverables, supporting career growth, and ensuring high-quality analytics output You will analyze audience growth, traffic drivers, customer journey touch points, and user engagement trends to inform strategic decision-making. You will partner with functional leads (Product, Design, Engineering, Editorial) to set strategy, define goals, and build the audience and product analytics roadmap. You will lead the design, execution, and post-analysis of product experiments (A/B testing). Provide expertise on primary metrics, trade-offs between competing goal

🚀 About WRITER WRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence. And we're proving it's possible – through powerful, trustworthy AI that unites IT and business teams together to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents that are grounded in their company's data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by industry-leading investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as the leader in enterprise generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Seattle, Austin, Chicago, and London, our team thinks big and moves fast, and we're looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work with AI. 📐 About the role Every company grows differently, and at WRITER, our growth is directly tied to empowering our users to create better content, faster, and at an unprecedented scale. As a strategic solutions architect, you'll be at the forefront of this mission, working directly with our largest and most strategic prospects to identify, validate, and build innovative agentic AI solutions that unlock massive business value. This isn't just about selling a product; it's about deeply understanding complex enterprise needs and architecting a future where AI transforms how our customers operate. You'll be instrumental in shaping how the world's leading companies adopt and scale AI, making a tangible impact on both their success and WRITER’s continued leadership in the enterprise generative AI space. This is a full-time, hybrid role based out of our Chicago hub. You will report directly to the Director, solutions architecture. 🦸🏻‍♀️ What you'll do Drive strategic technical discovery

Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,400 firms in nearly 60 countries use Addepar to manage and advise on nearly $9 trillion in assets. Its open platform integrates with nearly 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, London, Edinburgh, Pune, Dubai, Geneva, Singapore and São Paulo. The Role Did you know? Alternative investing has the potential to generate higher returns compared to traditional investments over the long term. AI and Machine Learning are revolutionizing the way alternative investments are managed and analyzed. Investors are using these technologies to gain insights, see opportunities, and optimize their investment strategies. Addepar is building solutions to support our clients' alternatives investment strategies. The alternatives data management product is a serverless, modular and terraformed stack. We're hiring a Senior Software Engineer to design, implement and deliver modern software solutions that ingest and process ML-extracted data. You will collaborate closely with cross-functional teams including data scientists and product managers to build intuitive solutions that revolutionize how clients experience alternatives operations. You will work closely with operations engineering on document-based workflow automation and peer engineering teams to define the tech stack. You will iterate quickly through cycles of testing a new product offering on Addepar. If you've crafted scalable systems, or worked with phenomenal teams on hard problems in financial data, or are just interested in solving reall

OUR MISSION At Redwood, we empower our customers with lights-out automation for their mission-critical business processes. ABOUT US Redwood Software is the leading orchestration platform for the autonomous enterprise, driving business transformation at the lowest total cost of ownership. Redwood empowers organizations to intelligently automate and orchestrate mission-critical business and IT processes across complex ERP, hybrid cloud, data and emerging agentic AI systems. Through its SaaS-first automation fabric—with AI embedded across the automation lifecycle—Redwood accelerates the path to autonomous operations. Backed by 30 years of experience and trusted by more than 50% of the Fortune 50, Redwood helps organizations unlock human potential to focus on innovation, growth and what’s next. CORE VALUES One Team. One Redwood Make Your Own Weather Obsess over Customer Success Work the Problem Be Curious Own the Outcome Respect Each Other YOUR IMPACT As a Senior Full Stack Software Developer, you will be responsible for leading the design, development, and delivery of scalable full-stack applications, shaping system architecture, and driving engineering excellence across Redwood’s automation and SaaS platforms. Design, develop, and implement scalable, secure, and high-performance full-stack applications using Java, JavaScript, and related technologies Architect and build backend services, APIs, and microservices with a focus on scalability, reliability, and maintainability Develop responsive, accessible, and high-quality front-end user experiences Partner with product managers and stakeholders to define technical strategy and translate business requirements into system designs Own and contribute across the full software development lifecycle, from architecture and design to deployment and optimization Establish and promote best practices in coding, testing, observability, performance optimization, and AI usage Lead architectural discussions a

PagerDuty (NYSE:PD) is a leader in Digital Operations Management. In an always-on world, organizations of all sizes trust PagerDuty to help them deliver a perfect digital experience to their customers, every time. Teams use PagerDuty to identify issues and opportunities in real time and bring together the right people to fix problems faster and prevent them in the future. Over 13,000 organizations (including 60 of Fortune 100) rely on PagerDuty to succeed with Digital Transformation, Cloud Migration, and DevOps Modernization. Notable customers include GE, Cisco, Genentech, Electronic Arts, Cox Automotive, Netflix, Shopify, Zoom, DoorDash, Lululemon and more. We are expanding rapidly as a platform for Digital Operations Management using AI/ML and Automation and growing our adoption by Development, IT, Customer Service, Security, and other teams across the organization. PagerDuty is looking for a Machine Learning Engineer who is passionate about collaborating with data scientists, product managers and engineers alike. As part of our team, you will help us accelerate the development and extension of products powered by Gen AI and many other shapes of Machine Learning. You’ll be contributing hands-on to the development of the services and pipelines that enable multiple ML/AI features in our product. You will have the opportunity to collaborate with multiple organizations, taking input and guidance from your senior stakeholders and helping bring our initiatives to reality. You’ll succeed by showcasing excellent capacity to manage time, demonstrating emotional intelligence as you navigate stakeholder relationships, and by continuously improving your technical skill set. Key Responsibilities Build and improve the capabilities that enable and accelerate the production of machine learning (ML) and generative AI (genAI) based solutions Partner with data scientists, effectively sharing engineering context and collaborating to support larger initiatives Incorporate the best ava

PagerDuty (NYSE:PD) is a leader in Digital Operations Management. In an always-on world, organizations of all sizes trust PagerDuty to help them deliver a perfect digital experience to their customers, every time. Teams use PagerDuty to identify issues and opportunities in real time and bring together the right people to fix problems faster and prevent them in the future. Over 13,000 organizations (including 60 of Fortune 100) rely on PagerDuty to succeed with Digital Transformation, Cloud Migration, and DevOps Modernization. Notable customers include GE, Cisco, Genentech, Electronic Arts, Cox Automotive, Netflix, Shopify, Zoom, DoorDash, Lululemon and more. We are expanding rapidly as a platform for Digital Operations Management using AI/ML and Automation and growing our adoption by Development, IT, Customer Service, Security, and other teams across the organization. PagerDuty is looking for a Machine Learning Engineer who is passionate about collaborating with data scientists, product managers and engineers alike. As part of our team, you will help us accelerate the development and extension of products powered by Gen AI and many other shapes of Machine Learning. You’ll be contributing hands-on to the development of the services and pipelines that enable multiple ML/AI features in our product. You will have the opportunity to collaborate with multiple organizations, taking input and guidance from your senior stakeholders and helping bring our initiatives to reality. You’ll succeed by showcasing excellent capacity to manage time, demonstrating emotional intelligence as you navigate stakeholder relationships, and by continuously improving your technical skill set. Key Responsibilities Build and improve the capabilities that enable and accelerate the production of machine learning (ML) and generative AI (genAI) based solutions Partner with data scientists, effectively sharing engineering context and collaborating to support larger initiatives Incorporate the best ava

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role We’re looking for a Senior Applied Scientist to help drive the future of credit applied science at Ramp. In this role, you will design, build, and optimize the models that power our credit risk systems, helping us make faster, smarter, and more scalable risk decisions for our customers. You’ll work at the intersection of machine learning, statistics, economics, and product strategy. This role requires strong technical depth as well as close collaboration with business, product, data, and engineering partners. You will help identify high-impact opportunities, translate ambiguous business problems into rigorous modeling work, and ship models that operate reliably in production. Applied scientists at Ramp focus on solving quantitative problems across credit, fraud, growth, and our core product by applying the right mix of machine learning, causal inference, structural modeling, and optimization. What You'll Do Design, build, and optimize machine learning models that support credit risk decisioning and portfolio management at Ramp Own the

We are a global team of innovators and pioneers dedicated to shaping the future of observability. At New Relic, we build an intelligent platform that empowers companies to thrive in an AI-first world by giving them unparalleled insight into their complex systems. As we continue to expand our global footprint, we're looking for passionate people to join our mission. If you're ready to help the world's best companies optimize their digital applications, we invite you to explore a career with us! Your opportunity At New Relic, we provide our customers real-time insights, so they can innovate faster. Our software delivers insightful observability tools across different technologies and distributed systems, enabling software engineering teams to quickly identify, understand and tackle issues, analyze performance and get the most of their software and infrastructure. Database Observability is a critical pillar of New Relic's platform strategy. We are looking for an experienced Engineering Manager (M3) to lead a senior, high-performing team building next-generation Database Observability products. Your team will own the entire lifecycle of critical telemetry data flows from lightweight database agents and high-throughput ingestion pipelines to intelligent DB recommendation engines and autonomous DB AI Agents. You will lead a team that includes senior and Lead-level engineers with deep domain expertise in distributed systems and AI. Your primary value will come from setting strategic technical direction, enabling their best work, and fostering a high-accountability culture while partnering closely with Product and Design to deliver features that directly drive New Relic's Database Observability. What you'll do Manage a full-stack engineering team (6–8 engineers) spanning backend systems, database telemetry, agent engineering, and UI workflows. Own end-to-end delivery sprint planning, roadmap execution, system quality, and operational excellence for critical database ingesti

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . What you’ll do: Be the technical lead for the forecasting team . Own the strategy and implementation of forecasting models of key company metrics (e.g., monthly active users), delivering accurate, interpretable forecasts at scale. Lead the full modeling lifecycle end to end : problem framing, feature engineering, model development and prototyping, experimentation and backtesting, deployment, monitoring/drift detection, and explainability. Set the forecasting technical vision. Define model architectures and standards, and partner with Engineering to shape the forecasting platform for efficient training/inference today and the scalability needed for the next generation of models. Translate forecasts into decisions. Present outputs, scenario analyses, and recommendation frameworks to senior leadership with clarity and brevity. This is a high‑visibi