About the Role

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.

This is a small team at a small company. You'll make architectural decisions with real consequences and work across the full data stack, from ingestion through modeling. This isn't a role for someone who wants deep specialization in one area.

What You'll Do

• 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

What You Bring

• 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.

Nice to Have

• 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

Recruitment Process

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:

1. Recruiter Screen

2. Take-Home Assignment

3. Technical Interview

4. Culture Add Interview

5. Offer & Background Check

We welcome applications regardless of gender, nationality, ethnic origin, religion, disability, age, or sexual identity. Diversity is key to producing high-quality intelligence.