Data Engineer in Ireland

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

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The Developer Productivity group is responsible for making Stripe’s developers happy and productive. We work on tools, processes, and code refactoring to accelerate Stripe engineering as Stripe scales. We’re looking for people with an interest in building the tools to improve the day to day experience of Engineers in Stripe. The ideal candidate will have a passion for solving developer experience problems, and a pragmatic ability to ship results iteratively—powered by a mix of technical expertise across some or all of: language processing tools; version control systems; build systems; and distributed systems engineering. You’ll be working on a mix of engineer-facing systems, CI infrastructure platforms, and big-data engineering. What you’ll do We have a ton of important work to do, which is why we’re hiring! Our active projects change all the time, but here are a few examples of recent projects so you can get an idea of the types of work we do: Build and manage systems to handle CI at massive scale—including batching, speculative stacking, merge-race inhibition, and more. Build and manage systems to handle our enormous CI test suite–identifying and managing flaky tests, assessing and reproducing flakiness, and optimizing for test effectiveness. Enhance our CI systems for reliability, including adaptive response to available capacity, resilience and self-recovery from outages, and highly-leveraged observability. Detect and isolate code breaka

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

As Senior Data Scientist for Engineering Systems you will work independently alongside sharp, generous, and pragmatic engineers from Server Query, Atlas Clusters, and Release Quality, among other teams. Together, we tackle problems spanning resource scaling across the Atlas fleet, safe feature rollout to MongoDB clusters, automated incident response and query engine performance. Join the Platform Data Science team and help us research, prototype and ship machine learning features for MongoDB’s core server, query engine and Atlas, our database-as-a-service cloud offering. We are looking to speak to candidates who are based in Dublin or Cork for our hybrid working model. What You'll Do Partner with Server Query, Atlas Clusters, Release Quality and other engineers to embed algorithmic rigor and optimization into resource scaling, release-safety and monitoring systems across the fleet and inside query engine Deliver production-ready, thoroughly tested statistical and ML algorithms with well-identified limitations that deliver measurable business impact, not just an impressive-sounding methodology Own the full feedback loop: instrument model architecture with the metrics needed to track performance and create dashboards in collaboration with our stellar analytics team, collect feedback from users and metrics to diagnose issues or opportunities, and iterate accordingly Deliver thoughtful, kind code reviews to your peers and act as a core contributor to internal packages, tooling, and team processes that increase developer productivity Measures of Success In 3 months, you’re familiar with our workflow, have an elementary understanding of our product and what teams we work with. You have delivered small-to-medium improvements to our project portfolio In 6 months, you’ve delivered one feature you researched and prototyped from scratch and demonstrated its impact on business metrics of your choice In 12 months, you've established a track record of shipping ML-driven improveme

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 . We are looking for inquisitive, well-rounded Senior Full-Stack and Backend engineers to join our Data and Core engineering teams. Working closely with product managers, designers, and backend engineers, you’ll play an important role in enabling the newest technologies and experiences. You will build robust frameworks & features. You will empower both developers and Pinners alike. You’ll have the opportunity to find creative solutions to thought-provoking problems. Even better, because we covet the kind of courageous thinking that’s required in order for big bets and smart risks to pay off, you’ll be invited to create and drive new initiatives, seeing them from inception through to technical design, implementation, and release. What you’ll do: Build out the backend for Pinner-facing features to power the future of inspiration on Pinterest Con

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

MongoDB is seeking an Engineering Manager to join the Atlas Growth Team. The team is responsible for improving and creating new features for MongoDB Atlas, our developer data platform that accounts for 65% of the company’s revenue. Atlas allows users to deploy fault-tolerant, secure, globally distributed MongoDB clusters in just minutes. The Atlas Growth team focuses on improving the customer experience via new product experiences and refinements to existing user flows. The team works closely with cross-functional partners, as well as other MongoDB engineering teams to bring new visions to life. We are constantly challenged to design features such as new onboarding flows, monetization improvements, and advanced cluster management tools for our large B2B customer base. We are looking to speak to candidates who are based in Dublin for our hybrid working model. What You’ll Do Manage a team of engineers to design, build and test new features for MongoDB Atlas Contribute to and lead complex technical projects Work with cross-functional stakeholders to design the team's roadmap, defining delivery dates that balance technical feasibility with the pace of the market Work closely with product, design and analytics teams, considering the user’s perspective while building technical solutions Collaborate with team members to develop our codebase, best practices, and design principles Learn from and mentor an impassioned array of team members We’re Looking for Someone Who Has at least 5 years of professional software development experience Has at least 2 years of people management experience Is skilled at writing large-scale, distributed backend systems in a compiled language (Java, C#, Go, etc.) Is comfortable working across the stack of a modern web application (e.g. React, TypeScript, React Testing Library) Has experience with at least one major cloud provider technology (AWS, Azure, GCP) Has a deep understanding of product analytics Has experience with A/B testing and