Senior Data Engineer

Our data infrastructure was built from scratch on DigitalOcean with no managed services. Custom containerized microservices and hand-rolled message queues, manually maintained end-to-end. It works, but we've outgrown it, and the migration to AWS is underway.

You'll join the Data team to keep the current platform running while leading the migration to AWS managed services. This is a dual mandate: maintain what exists and build what replaces it., * Own the DigitalOcean-to-AWS migration: plan the transition from custom-built infrastructure to managed services and execute it without breaking production

• Keep the lights on: while migrating, maintain legacy services, manage Docker containers, handle library and version updates across the existing platform
• Build and evolve data pipelines: ingestion, processing, and modeling for cybersecurity intelligence data that feeds our Mercury analytics platform and analyst workflows
• Collaborate with Threat Intelligence Engineers on data access patterns, tool integration, and source modifications as business priorities shift
• Shape the team's technical direction: with two engineers on the data side, your judgment carries weight, We aim to be as transparent as possible throughout the process and provide you with frequent updates when there is progress on our end. In order to manage your expectations transparently, we have structured the recruitment process as follows

• Experience building infrastructure in resource-constrained environments: you've set up data systems from nothing, not only maintained or extended existing ones. This is the qualification we weigh highest.
• Cloud platform experience (AWS, GCP, or Azure): you understand managed services well enough to decide when to use them and when not to
• Python as a working language for data engineering
• Golang - working familiarity
• Docker and containerized services: deploying, debugging, and managing containers is routine for you
• Microservices architecture or distributed systems: you've designed or maintained service-oriented systems, not only monoliths
• Data engineering fundamentals: you can reason about data pipelines from ingestion through modeling
• Comfort with AI-assisted development (Copilot, Claude, Cursor)

You'll also need professional English proficiency (the team works across countries) and genuine comfort with startup ambiguity. QuoIntelligence is ~40 people, Series A stage., * AWS-specific experience (migration experience is a strong plus)

• Redis or ZMQ for message queuing
• Legacy system maintenance experience to help us keep aging infrastructure healthy while building replacements
• Cybersecurity or threat intelligence background

Founded in Germany in 2020, QuoIntelligence is Europe's leading provider of Unified Risk Intelligence - a strategic fusion of Threat Intelligence, Digital Risk Protection, and Risk Intelligence services. We enable organizations to proactively identify and mitigate cyber, geopolitical, and physical risks with intelligence tailored to their unique threat landscape. Unlike traditional feed-based solutions, every client benefits from our analysts' work supported by Agent Karla's automation and our proprietary Mercury platform, ensuring high-quality intelligence with low operational friction. Deeply embedded in the European regulatory and operational context, and with legal entities in Germany, Italy, and Spain, QuoIntelligence is the trusted partner to critical infrastructure operators, significant financial institutions, government agencies and enterprises across the EU.