Data Engineer 2c Data Foundations Specialist in Ireland

GTM Operations & Strategy at MongoDB is a global team of builders and innovators focused on unleashing MongoDB’s sales greatness by pairing world‑class analytics with scalable operations. Within GTM Operations, the GTM Intelligence – Applied Science team turns complex GTM data into tools, models, and insights that help our sales organization make better, faster decisions across our people, segmentation, territory design, forecasting, and account prioritization. As a Senior Analyst on the Applied Science team, you will own high‑impact analytical workstreams end‑to‑end: from problem framing with senior GTM stakeholders, to data engineering and model design, through to productionalized workflows, dashboards, and executive‑ready narratives that drive concrete changes in the field. This role is based in Dublin, Ireland and supports a global stakeholder set across regions and GTM functions. We are looking to speak to candidates who are based in Dublin or Cork for our hybrid working model. What You’ll Do Translate GTM questions into analytical projects Partner with GTM Ops, Sales Strategy & Planning, Sales Leadership, and Central Analytics to scope problems, define success criteria, and prioritize work across areas like segmentation, territory design, account prioritization, and pipeline/forecast health. Structure ambiguous questions into hypotheses, analytical plans, and clear recommendations for senior stakeholders (SVPs, RVPs, functional leaders). Design and build scalable analytics & models Develop and maintain statistical and machine learning models (e.g., NARR prediction, deal qualification, account momentum, workload identification) that inform forecast expectations, territory assignments, and deal prioritization. Engineer robust data pipelines and features (SQL/Python) on top of our GTM data stack (Salesforce, product usage, call transcripts, marketing signals, etc.) in partnership with data and platform teams. Own core GTM analytics assets Contribute t

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 . Pinterest's Data Privacy Engineering team builds access control, auditing, and data handling services and solutions used across the company to power Pinterest experiences. AI is transforming how software is built, data is analyzed, and users interact with software. We're looking for a Senior Engineer based in Dublin to help build the next generation of Data Privacy solutions for AI platforms, ensuring agents interact with data responsibly and transparently. What you’ll do: Design services and processes used to safely onboard new AI use cases Create isolated environments to enable secure agent-driven data processing without direct data exposure Design and maintain an auditing pipeline to monitor and log all AI sandbox data egress Collaborate cross-functionally with engineering teams across Pinterest to identify and tackle new data privacy c

The data management software market is transforming how organisations build and run applications. MongoDB is the leading developer data platform and the first database provider to IPO in more than 20 years. Join us at the forefront of data and application development. MongoDB Technical Services Engineers combine deep technical expertise with exceptional problem-solving and customer-service skills. You’ll advise customers and resolve complex challenges across MongoDB Core, drivers, Atlas, Cloud Manager, cloud platforms, and infrastructure. We’re looking for candidates based in Dublin to join our vibrant office and collaborative in-office team. This is a five-day role with one of the following schedules: Tuesday–Saturday, Sunday–Thursday, or a five-day pattern covering both Saturday and Sunday. Under our hybrid model, employees on weekend schedules are expected to work from the office two days per week. Cool things you’ll do You’ll help customers troubleshoot complex issues and run critical MongoDB workloads with confidence. You’ll: Solve customer challenges across architecture, performance, recovery, and security Lead investigations from diagnosis to resolution, providing clear, actionable guidance Partner with Product Management and Engineering to advocate for customers and improve MongoDB Build tools, documentation, and training while mentoring peers and raising technical excellence What you need We value curiosity, adaptability, strong technical foundations, and a genuine desire to help customers. You should bring many of the following: 5–6 years of experience in technical support, systems engineering, database administration, SRE, or a related field Experience running complex, mission-critical production database systems Strong Linux and systems engineering skills, including performance, memory, I/O, storage, networking, security, clustering, and troubleshooting A solid understanding of networking concepts and protocols, including DNS, TCP/IP, and SSL/TLS Ability

The worldwide data management software market is massive, forecasted to grow from approximately $82 billion in 2023 to approximately $137 billion in 2027. At MongoDB, we are transforming industries and empowering developers to build amazing apps that people use every day. We are the leading developer data platform and the first database provider to IPO in over 20 years. Join our team and be at the forefront of innovation and creativity. We are looking for a Technical Services Engineer to join our team in Dublin for a dedicated Tuesday through Saturday shift. We are looking to speak to candidates who are based in Dublin for our hybrid working model. About the Team MongoDB Technical Services Engineers (TSEs) use their exceptional problem-solving and customer service skills, along with deep technical experience, to advise customers and solve complex MongoDB problems. TSEs are experts in the entire MongoDB ecosystem, including the database server, drivers, and services like Atlas and Cloud Manager. Our engineers combine MongoDB expertise with passion, initiative, and teamwork to achieve exceptional results. Cool Things You’ll Do Work alongside our largest customers and partners to solve complex issues involving architecture, performance, recovery, and security Serve as an expert resource on standard methodologies for running MongoDB at scale Act as an advocate for customer and partner needs by collaborating with product management and development teams Contribute to internal projects, such as the software development of support tools for performance, benchmarking, and diagnostics Mentor and ramp up new team members while building knowledge of new product lines within the MongoDB ecosystem Work with top ISV partners to ensure excellence for joint customers What You Need Solid hands-on experience with systems engineering, including Linux performance, memory management, I/O tuning, configuration, security, networking, and troubleshooting A strong understanding of net

Join the MongoDB Server Query team, and help us build a world-class distributed open source query engine. Our team plays a crucial role in the experience and performance of data processing. We are responsible for the MongoDB Query Language and the lifecycle of each query, from parsing to optimization to plan selection and finally execution. This also includes our geospatial search and update subsystems. Our global team is growing fast. In North America, we have a presence across the US and Canada including New York, West Coast, Toronto. In Europe, we have a presence in Dublin, Germany, France, Netherlands, UK, Bulgaria, Spain and Italy currently. We support office-based and remote work and align projects with convenient work hours for each time-zone. We have tons of interesting problems to solve with direct impact on users for transactional, time-series and analytical workloads. We need your help to design and build the heart of a distributed, flexible schema, document database. We are looking to speak to candidates who are based in Dublin or Cork for our hybrid working model. Candidate Profile 3+ years of experience in data intensive environments Hands-on experience building industrial-strength software Solid computer science fundamentals, with strong competencies in data structures, algorithms, and software design/architecture Experience with large code bases B.Sc in Computer Science or similar field, or equivalent practical experience Experience in C++ and in developing database systems is a plus Interest in the theory and practice of database query engines. Hands-on experience or M.Sc./Ph.D in the domain is a plus Position Expectations Understand and improve current functionality of the MongoDB query engine Identify, design, implement, test, and support new features related to query performance and robustness, query language enhancements, diagnostics for query performance problems, and integration with other products and tools Work with other engineers to

Atlas Growth is a cloud engineering group whose mission is to guide customers through their app development journey—from cluster configuration, data modeling and load testing, to running a production workload at scale. We use an in-house experiments platform which helps us validate our features quickly, releasing only the work that positively impacts our customers. Our engineers participate in cross-functional “squads” with product, design, analytics, and research focusing on a single metric (e.g. retention). Our engineering team is part of a larger Atlas Core Engineering org, building foundational elements of MongoDB’s developer data platform. Atlas Growth 2 builds customer-facing features in Atlas and sits alongside other Growth engineering teams. Recent projects include an AI Chatbot for cluster creation, a recommendation system that offers tips for better database performance, and a pricing page designed to optimize conversion rates. We are looking to speak to candidates who are based in Dublin for our hybrid working model. Role Overview Atlas Growth seeks a mid-level software engineer (Software Engineer 3). SE3s are solid contributors to projects they work on and often lead projects of their own. They act in accordance with MongoDB’s core values and leadership principles, and are actively working toward a Senior role. Candidate Profile 3+ years of software engineering experience, with fluency in TypeScript/JavaScript, and experience with a modern framework (e.g. React) Proficiency in Java, Go, C++/C, or a similar compiled language is a plus Experience writing database queries, either document-based or relational Experience writing and reviewing technical specs, and leading small projects Interest in A/B testing or product design Expectations Contribute readable and well-tested code to ongoing projects Collaborate closely with product and design partners to implement and iterate on new customer facing features Write scope and technical spec docs for new projects

About the Team The Privacy Engineering team builds secure, reliable systems that help OpenAI meet its legal obligations while protecting user data. We partner closely with Legal and engineering teams across OpenAI to support lawful data access requests and other critical legal workflows. Our work turns complex, high-stakes processes into auditable and dependable technical systems with clear human oversight and strong privacy and security controls. About the Role We’re looking for a full-stack Software Engineer to build the internal tools and data pipelines that power lawful data access request workflows and Legal Operations. You will work across product and data systems to make authorized retrieval and case handling accurate, efficient, and auditable. This role is well suited to someone who enjoys translating ambiguous operational requirements into durable systems, cares deeply about sensitive-data handling, and wants to improve both technical reliability and the day-to-day experience of the people operating these workflows. In this role, you will: Design, build, and operate backend systems and workflow tooling for the full lifecycle of lawful data access requests, from intake and scoping through authorized retrieval, review, preparation, and audit. Build reliable data pipelines and interfaces across products and data stores so authorized teams can locate and handle the right records accurately and reproducibly. Implement least-privilege access, approval gates, provenance, audit trails, data minimization, and safe failure modes for sensitive workflows. Partner with Legal and Legal Operations to translate legal and operational requirements into clear technical designs and intuitive operator experiences. Identify responsible automation opportunities that reduce repetitive work while preserving human review, judgment, and accountability. Own production systems through testing, observability, incident response, documentation, and continuous reliability improvements. Hel

About the Team The Privacy Team at OpenAI is committed to building a secure and trustworthy platform. Our area of responsibility encompasses all OpenAI products and systems that process user data. We provide cross-functional partners with the tools needed to ensure that all products adhere to the highest standards of data privacy and legal compliance. Our approach to prioritizing responsible data use is integral to OpenAI's mission of safely introducing Artificial General Intelligence (AGI) that offers widespread benefits. About the Role We’re in search of a Software Engineer with experience building data pipelines and working closely with members of the Legal team. This role is perfect for someone who's passionate about the intersection of systems, privacy, and legal compliance. You will architect, design, and write backend systems responsible for handling some of the most sensitive data at OpenAI. This role is based in Dublin, Ireland. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, build, and maintain back-end systems and services that power privacy and data compliance functions within our API products and consumer applications. Work closely with legal advisors and other engineers to respond to court orders and other legal processes, all while upholding strict data privacy and legal standards. Identify opportunities for automation and build the tools that enable other teams to automate tasks involving customer data. Develop and implement data handling policies and procedures in compliance with legal and ethical standards, ensuring the integrity and confidentiality of user data. You might thrive in this role if you: Have experience building data pipelines, especially for legal processes and investigative workflows. Can translate legal requirements into technical solutions and explain technical solutions to a non-technical audience. Take responsibility for problems from be

We are seeking a Staff engineer to design, build, and operate the internal and external Observability stack for the MongoDB platform. Tens of thousands of customers depend on our Observability stack to monitor their database clusters and to generate actionable alerts to safeguard critical workloads. The Collections team is a newly formed team within MongoDB's Observability & Adoption Org focused on making telemetry onboarding and collection significantly easier across MongoDB. We own key parts of the observability collection stack, including onboarding experience, telemetry collection agents across the data and control planes, and ingestion services for metrics, logs, and traces that support both internal and customer observability in MongoDB, driving insights, recommendations, and alerting. Our mission is to reduce friction for teams implementing and iterating on Observability while partnering closely with development teams to instrument their services using shared best practices, helping define the conventions our telemetry should follow, and building collection and ingestion systems that are stable, performant, secure, well-documented, and self-service. We also work closely with the Data Pipeline and Storage & Query teams to help ensure MongoDB has a stable and performant observability stack end to end. This is an opportunity to join a team shaping how observability works across MongoDB and to have outsized impact on both the developer experience and the reliability of the platform underneath it. As MongoDB Atlas and its supporting infrastructure continue to experience rapid growth, the demand for high-cardinality observability data for internal and external use cases means we need to continually innovate and scale our systems to the next level. For example, MongoDB Observability systems need to handle 10’s of billions of metrics time series, all whilst processing petabytes of logs, traces, and events. Our stack includes VictoriaMetrics, Grafana, Sp

We are seeking a Staff engineer to design, build, and operate the internal and external Observability stack for the MongoDB platform. Tens of thousands of customers depend on our Observability stack to monitor their database clusters and to generate actionable alerts to safeguard critical workloads. This is an opportunity to join a team that is responsible for all Observability systems that support metrics, metric visualization, logs, traces, and alerts for MongoDB. We are looking for engineers with high standards, and experience in setting direction and technical leadership for large engineering teams in designing and operating complex distributed systems, with strict SLO on security, durability, availability and performance. As MongoDB Atlas and its supporting infrastructure continue to experience rapid growth, the demand for high-cardinality observability data for internal and external use cases means we need to continually innovate and scale our systems to the next level. For example, MongoDB Observability systems need to handle 10’s of billions of metrics time series, all whilst processing petabytes of logs, traces, and events. Our stack includes VictoriaMetrics, Splunk, Flink, WarpStream/Kafka, Java, Golang Fluentbit. In addition to owning critical components of our observability infrastructure, as a Staff engineer on the team, you’ll also work closely with other SWE, Product and SRE teams to promote and implement best practices in instrumenting and monitoring their services. This is a highly collaborative role, and you will get to own some of the most relied upon internal infrastructure at Mongo. Our team champions a strong culture of inclusivity, diversity, and collaboration. If you want to be a deeply technical leader on a collaborative team that applies low-level systems expertise to build the foundational infrastructure of a popular database, join us! Let’s build a faster, more reliable, and exceptionally observable database system together. W

We are seeking a Staff engineer to design, build, and operate the internal and external Observability stack for the MongoDB platform. Tens of thousands of customers depend on our Observability stack to monitor their database clusters and to generate actionable alerts to safeguard critical workloads. The Collections team is a newly formed team within MongoDB's Observability & Adoption Org focused on making telemetry onboarding and collection significantly easier across MongoDB. We own key parts of the observability collection stack, including onboarding experience, telemetry collection agents across the data and control planes, and ingestion services for metrics, logs, and traces that support both internal and customer observability in MongoDB, driving insights, recommendations, and alerting. Our mission is to reduce friction for teams implementing and iterating on Observability while partnering closely with development teams to instrument their services using shared best practices, helping define the conventions our telemetry should follow, and building collection and ingestion systems that are stable, performant, secure, well-documented, and self-service. We also work closely with the Data Pipeline and Storage & Query teams to help ensure MongoDB has a stable and performant observability stack end to end. This is an opportunity to join a team shaping how observability works across MongoDB and to have outsized impact on both the developer experience and the reliability of the platform underneath it. As MongoDB Atlas and its supporting infrastructure continue to experience rapid growth, the demand for high-cardinality observability data for internal and external use cases means we need to continually innovate and scale our systems to the next level. For example, MongoDB Observability systems need to handle 10’s of billions of metrics time series, all whilst processing petabytes of logs, traces, and events. Our stack includes VictoriaMetrics, Grafana, Sp

About the Team The Applied AI Engineering team is responsible for helping developers and enterprises safely and effectively deploy OpenAI technologies in production. We act as trusted technical advisors and thought partners for customers, working side by side with their teams to identify high-value use cases, design practical architectures, and move from prototype to durable deployment. Cybersecurity is one of the most urgent domains where AI can help. Security teams are under pressure to reason across code, logs, infrastructure, tickets, alerts, and vulnerability data faster than ever. As frontier models become more capable, organizations need deep technical guidance on how to evaluate, validate, and safely deploy AI systems in security-critical workflows. About the Role We are looking for a Cybersecurity Applied AI Engineer to partner with customers and help them apply OpenAI models, APIs, Codex, and agentic workflows to real cybersecurity use cases. You will work with CISOs, security executives, application security leaders, SOC teams, security engineering teams, and hands-on practitioners to identify where AI can create measurable security outcomes. This is a customer-facing technical role for someone who can move fluidly between executive strategy, practitioner-level cyber depth, and hands-on solution design. You will help customers evaluate and deploy workflows such as secure code review, vulnerability triage, threat modeling, remediation, SOC and incident response workflows, detection engineering, cloud security, GRC automation, and security validation. You will collaborate closely with Sales, Solutions Engineering, Product, Engineering, Research, and Security to turn customer needs into safe deployment patterns, reusable field assets, and product feedback. This role is based in our Dublin Office. We offer relocation support to new employees. In this role, you will: Deeply embed with strategic customers as the technical lead for AI-enabled cybersecurity workf

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams. Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers. What's the opportunity? Principal Engineers at Fin have the opportunity to lead the definition and execution of key strategic initiatives. You will work autonomously and be accountable for strategic execution in part of the engineering organization. You will build both back-end and front-end systems, and work closely with designers, product managers, researchers, and data analysts. You will coach and mentor other engineers and partner closely with the Group Engineering Managers on technical strategy and leadership. Learn more about our engineering culture at intercom.engineering What will I be doing? As an experienced engineer you will: Have a mastery of domain knowledge and work as a leader within the R&D org to drive key strategic projects. Provide assessments of project progress, risks and challenges to engineering leadership to help guide resource allocation and prioritisation. Contribute to our technical architecture as we grow. We scale to service requests from all our cus

MongoDB is looking for an outstanding person to join our newly created Forward Deployed Engineering team and take on a key role in our extended R&D organization. Forward Deployed Engineering is linking the work of teams engaged on application modernization roles with our Product and Engineering teams. We are looking to speak to candidates who are based in Dublin for our hybrid working model. Many organizations have built up large estates of legacy applications. Lack of scalability and resilience, long development times, operating cost, and inability to run on cloud are common issues with these applications. To address these issues, organizations are engaging in large transformational Application Modernisation programs. MongoDB is recognized as the developer data platform of choice for transactional systems that provide the best scalability, resiliency and developer experience in the cloud as well as on premises. Organizations are continuously migrating workloads from these legacy applications to new platforms, often based on microservices, using MongoDB. Such transformations are time intensive and often risky. Tooling based on generative AI promises to accelerate these transformations in a way never seen before. Forward Deployed Engineering is responsible for exploring the possibilities of Generative AI technologies and providing invaluable feedback to MongoDB’s R&D teams to drive future capabilities of MongoDB and the MongoDB ecosystem. Application Modernization Engineers will work alongside project teams that are executing Application Modernisation projects with customers. The successful candidate will be responsible for evaluation, build, and applying tools in modernization projects, facilitating the usage of such tools and processes across the different project teams, identifying opportunities for tooling deployment, selecting potential 3rd party tools, contributing to the development of tooling prototypes and helping to shape the produ

The MongoDB Query Execution Team is hiring software engineers who want to join us in developing a high performing, reliable and modular distributed query system. Our engineers work on implementing and maintaining execution algorithms, building new query language features, tuning database performance, and more to power our customers' critical workloads. This role can be based out of our Dublin office or remotely in Ireland. Relocation can be supported. Position Expectations Understand and improve current functionality of the MongoDB query engine Contribute high quality C++ code and give and solicit feedback in code reviews Identify, design, implement, test, and support new features related to query performance and robustness, query language enhancements, diagnostics for query performance problems, and integration with other products and tools Work constructively with peers to deliver excellent technical solutions Candidate Profile 5+ years of experience in systems programming Experience in databases and/or data management systems is a huge plus, but not a requirement Hands-on experience building industrial-strength software Solid computer science fundamentals, with strong competencies in data structures, algorithms, and software design/architecture Experience with large code bases, preferably in C++, C, Rust or a similar compiled language B.Sc in Computer Science or similar field, or equivalent practical experience Interest in the theory and practice of database query engines. Hands-on experience or M.Sc./Ph.D in the domain is a plus Success Measures In three months you’ll have contributed to the development of a project slated for the next major version, as well as fixed a few bugs in a minor version of our latest stable release series In six months, you’ll have taken on code review responsibilities and are independently delivering complex functionality and squashing bugs independently In twelve months, you’re leading the development of a new major feature and are h