Python Developer

We're looking for Software Backend Engineers to join our Data Department, developers with strong backend engineering skills and a passion for building the services and infrastructure that power critical systems for users and partners. You will work at the intersection of software engineering, AI and business automation, helping turn insights and models into reliable, scalable systems used across Fever., Architect and Build: Design, implement, and maintain scalable microservices using Python (FastAPI/Django). You will take ownership of breaking down complex monoliths or building new services from the ground up, applying DDD principles. Master the Event Stream: Build robust, event-driven flows with Kafka. You will ensure that our events are durable, ordered, and processed idempotently, managing eventual consistency with care. Integrate at Scale: Design fault-tolerant integrations with third-party ecosystems (Meta Ads, Google Marketing Platform, Salesforce). You'll navigate rate limits, retries, and circuit breakers to maintain platform stability, even when external APIs are unpredictable. Bridge OLTP and OLAP: Work at the intersection of transactional applications and analytical data. You'll optimize PostgreSQL for operational efficiency while designing ingestion pipelines for Snowflake and Elasticsearch, using Airflow and dbt. Productionize Data Capabilities: Partner closely with Data Science, Machine Learning, and Data Engineering teams to ensure seamless integration of data sources and model infrastructure. Elevate the Bar: Lead thorough code reviews, write RFCs for key technical decisions, and mentor mid-level engineers. You'll champion testing strategies (unit, integration, contract testing) and advocate for clean, sustainable code architecture., Open Source: A history of contributing to open-source projects or maintaining your own libraries. The environment We're a fast-moving, impact-focused, and tech-driven team that partners closely with Data Science and Data Engineering. We care deeply about clean, maintainable code and building solutions that last. We prefer sustainable improvements over quick fixes. We foster a strong sense of ownership, with engineers taking ideas from design through delivery and supporting their services in production as they're adopted across teams. Collaboration is at the core of how we work: product, engineering, and data functions team up to turn ideas and models into reliable, user-facing capabilities.

Python Proficiency: You're confident working deeply in Python. You understand topics like the GIL, concurrency (asyncio), generators, and decorators, and you care about maintainable typing and thoughtful performance optimization. Architecture Patterns: You enjoy designing systems that are easy to evolve and test. You're comfortable applying Hexagonal Architecture to keep domain logic clean and decoupled, and you can leverage patterns like CQRS and the Transactional Outbox to support consistency and reliability in an event-driven environment. Database Polyglot: You have strong SQL fundamentals and know how to design for performance (PostgreSQL internals, indexing strategies). You also understand when tools like Redis (caching) or Elasticsearch (search/aggregations) are the right fit. Communication: You communicate clearly in English across audiences - from engineers to non-technical stakeholders - and you can explain your decisions in a structured way, backed by data and sound reasoning. Pragmatic mindset: You balance quality with impact. You're able to make thoughtful trade-offs, deliver iteratively, and keep an eye on long-term sustainability while moving at a good pace. Bonus points for AdTech/MarTech Experience: Familiarity with APIs from major marketing or CRM platforms (Meta, Google, Salesforce Marketing Cloud, etc.). Infrastructure as Code: Experience defining infrastructure using Terraform or AWS CDK. Data Engineering Crossover: Experience with data pipelines, Airflow, dbt, or data modeling in warehouse environments like Snowflake or BigQuery. ML & Internal Products: Experience building data or ML-powered internal services or automation platforms. Production Engineering: Experience with containerization (Docker) and orchestration (Kubernetes). You are comfortable debugging production issues using monitoring tools (Datadog, Prometheus, Grafana).

A compensation package consisting of base salary and the potential to earn a significant bonus for top performance Stock options plan 40% discount on all Fever events and experiences Home office friendly, location in Spain Health insurance and other benefits such as Flexible remuneration with a 100% tax exemption through Cobee English / Spanish Lessons Wellhub Membership Possibility to receive in advance part of your salary by Payflow Compensation package consisting of base salary and the potential to earn a significant bonus for top performance: Base Salary: 50.000 - 70.000EUR Total Compensation: 70.000 - 90.000EUR (Including Base, Variable, and Stock Options) About the process Fever aims to provide the best-fastest possible experience to our candidates. This is how it would look like: Talent Interview - 45min: An intro to Fever, our culture and a conversation about your background and experience. Technical interview - 2h: An in depth discussion about a technical challenge, from architecture to coding details. Engineering Manager Interview - 1h: A deep dive into your background and what you can expect on your day to day at Fever. Inscribirse en esta oferta Recibir ofertas similares por correo electrónico Al crear una alerta, aceptas nuestros Términos y condiciones y Política de privacidad, y el uso de cookies.