Data Infrastructure Engineer

Company Canaria is a technology startup providing high-quality, large-scale labor market data to the B2B market. Our mission is to power the next generation of solutions in recruitment, HR analytics, workforce planning, lead generation, healthcare, academic research, and finance by delivering the most comprehensive and accurate job market data available. Our advanced data mining, computing optimizations, and state-of-the-art NLP techniques let us process job market data at scale: over 1 billion unique job postings drawn from 200,000+ data sources, with 100+ fields per record. Our clients use this data to understand market trends, identify skill gaps, and connect people with the right opportunities. What You Will Do Own the design and implementation of robust data pipelines that form the backbone of our product. Design and operate the databases behind that product, across relational and non-relational models. Build and deploy scalable, cloud-native and serverless services on our cloud platform. Use containerization (Docker, and Kubernetes where it fits) to streamline deployment and operations. Ensure system quality through stress, integration, and end-to-end testing. Write clean, maintainable, well-documented code. Collaborate with engineers, data scientists, and product managers. Who You Are (Required) 3+ years building production backend or data-intensive systems. Bachelor's in Computer Science, Engineering, or equivalent practical experience. Highly proficient in Python and comfortable in a Unix environment (scripting and application development). Solid experience with at least one relational database (e.g. PostgreSQL) and at least one NoSQL store (e.g. MongoDB or Redis). Hands-on experience with at least one major cloud platform (AWS, Google Cloud, or Azure). Comfortable containerizing and deploying applications with Docker. Nice to Have Experience designing scalable back-end systems for data-intensive workloads. Kubernetes in production. Aerospike or other high-throughput key-value stores. RESTful API design and optimization. CI/CD pipelines and automated testing frameworks. Monitoring and logging tools (e.g. Prometheus, Grafana). Big data warehouses (BigQuery, Redshift). Asynchronous programming in Python. Web scraping (Scrapy) and browser automation (Playwright). Benefits High-end laptop. Annual performance bonus. Work with global teams (US, EU). Founders and colleagues with FAANG and top-institution backgrounds. Access to powerful on-prem and cloud compute for research. Professional development and growth opportunities. Hiring Process First call about the role & expectations (15 mins) Basic Python coding interview (1 hour) Technical interview (1 hour)