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Senior Data Engineer

Moonpay

Estimated Salary: $105K-$175K
Location: Lisbon / Krakow / London / Madrid / Barcelona / Bucharest / Cape Town
About MoonPay 🌖💸 Hi, we’re MoonPay. We’re here to onboard the world to Web3. Why? Because we think Web3 is a unique and democratising technology. It gives people back control of their money, digital identity, data, and property like nothing else before it. What we do We’re the leading infrastructure company in Web3. This means we offer our partners everything from payment solutions (we call them 'Ramps') to minting software for digital collectibles, like NFTs. And over 3 0 million people around the world now trust our products — just take a look on Trustpilot. We’re also big on collaborations. And we've worked on stunts, drops, and partnerships with some of the world's most prestigious and forward-thinking brands. But that’s not all. We have also built our own consumer app because we wanted to see if we could build a better Web3 account. It’s taken off in a big way, and we're working hard to continually improve it and to strive for perfection. So whatever your background, we’re sure there’s something for you here. Come help us build the future of Web3 and digital ownership. 🌔 About the Opportunity This is a hands-on technical leadership role with the opportunity to shape the future of our data platform. You will be responsible for designing and building the core systems to unlock value from our data as we grow.  We are looking for a passionate engineer who thrives on solving complex challenges, from high-level architectural design down to implementation. Your impact will come from tackling technical problems directly while also mentoring the team and influencing the long-term vision. 🚀 What you will do As a Senior Data Engineer on our Data Platform team, you'll be a critical player in the evolution of our data platform. You will be a hands-on technical expert, responsible for designing, building, and optimizing the core infrastructure and services that empower our developers and data users. Day-to-day, you will: * Design and develop key components of our data platform. This means getting hands-on to build and scale the robust foundations our data and AI capabilities rely on, including real-time streaming, orchestration, data warehousing, batch ingestion and governance. We value strong experience in at least one of these core areas. * Take ownership of the estimation, planning, and execution of complex data platform projects, including new feature development and major service upgrades. * Improve and scale our existing data platform codebase, data pipelines, and Infrastructure as Code (IaC), with a focus on enhancing scalability, reliability, performance, and cost-effectiveness. * Collaborate closely with engineering, analytics, and data science teams to understand their needs, gather requirements, and deliver reliable and well-adopted platform capabilities. * Write well-tested, high-quality, and performant code for data processing, platform automation, and infrastructure management. * Lead the design and delivery of complex data engineering projects, partnering effectively with stakeholders to drive these from concept through to successful implementation. * Mentor other engineers on the team, helping to elevate their skills and fostering best practices in data engineering through code reviews and technical guidance. * Uphold and contribute to high standards for code quality, testing, and documentation, and proactively identify and help manage technical debt. 💻 What you'll be working on Within our Data Platform team you will partner and collaborate across our Platform, Security and Data teams to shape and develop Moonpay’s data capabilities. Key Technologies you'll use daily: * Primarily Google Cloud Platform (GCP) – think Kubernetes, Kafka, Pub/Sub, Dataflow, Airflow, Cloud Storage, Datadog. (Experience with AWS/Azure is also great). * Languages: we primarily use Python, Terraform, Bash, SQL Types of projects and systems you'll focus on: * Real-Time Event Streaming: Enhancing and managing our infrastructure for handling high-volume, low-latency event streams * Shared Data Tooling & Frameworks: Creating reusable libraries, APIs, and services that make it easier and faster for other teams to build data-driven applications. * Core Data Pipelines: Building and scaling the systems that ingest, process, and make data available from various sources. * Platform Automation & Observability: Improving how we deploy, monitor, and manage our data infrastructure. * Data Governance & Quality Systems: Developing tools and processes to ensure our data is compliant, reliable, secure, and well-documented. * Data Warehousing: Designing, building, and optimizing how we store and model data for analytics and reporting. * ML Platform Enablement: Building and supporting the underlying infrastructure and data pipelines that our Machine Learning teams need. 🧑‍🚀 About You You are a skilled and experienced engineer with a passion for building robust, scalable, and impactful data solutions. You thrive in a collaborative environment and are driven to deliver high-quality systems while helping to elevate your teammates' skills. We’re looking for someone who brings: * A strong track record of building and delivering significant components of a data platform and data ingestion pipelines and frameworks. You have experience developing shared services that accelerate the work of internal users like engineers, analysts, and data scientists. * Proven experience in designing and implementing complex data systems and contributing to key technical decisions. * Hands-on experience with real-time/event-driven systems (e.g., Kafka, Pub/Sub), data warehousing/modeling, and orchestration tools (e.g., Airflow). * Proficiency with Infrastructure as Code (IaC) (e.g., Terraform) for managing complex, production-grade data infrastructure. * A team-first attitude; you enjoy mentoring others and sharing knowledge because you believe that rising tides lift all boats * Experience building platform capabilities that enable at least one of: self-service, real-time analytics, data governance, machine learning. * A continuous drive to stay current with data engineering technologies and best practices, applying them to solve real-world problems.
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