Summary

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 Staff Data Engineer on our Data Platform team, you'll be at the forefront of shaping our data platform. You'll be a key technical leader and contributor, shaping the future of how data is used. Your work will involve building and enhancing the core infrastructure and services that empower other developers and our data users.

Day-to-day, you will:

* Architect, design, and develop our data platform capabilities. This means getting hands-on to build the robust foundations our data and AI capabilities rely on. Including real-time streaming, orchestration, data warehousing and governance. We value deep expertise in at least two of these core areas.

* Actively contribute to our technical vision and roadmap, including the estimation, planning, and execution of complex data platform projects, including new service integrations and major infrastructure upgrades

* Contribute and improve our existing data platform codebase, data pipelines, and Infrastructure as Code (IaC), focusing on scalability, reliability, performance, and cost-effectiveness

* Collaborate across engineering and analytics teams to deliver reliable platform capabilities that directly empower them, and to ensure these services are well-adopted and impactful

* Work closely with engineers, analysts, and data scientists to understand their needs, define clear requirements, and develop effective implementation plans for platform enhancements

* Write well-tested, high-quality, and performant code for data processing, platform automation, and infrastructure management

As a Staff Data Engineer, you will also:

* Lead technical initiatives for the data platform from an engineering perspective, partnering effectively with stakeholders to drive these from concept through to successful delivery and adoption

* Mentor and coach engineers and other technical team members, helping to elevate their skills and fostering best practices in data engineering and system design

* Champion high standards for code quality, testing, and documentation within the data platform, and proactively identify and strategize on managing technical debt.

* Define and contribute to our overall data engineering standards, patterns, and best practices, including areas like data modeling, pipeline design, IaC, monitoring, and alerting for our data systems

💻 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.

Skills

• Communications Skills
• Development
• Leadership
• Python
• Software Engineering
• Strategic Thinking
• Team Collaboration