Data Engineer

? About usmscope is a fast growing fintech applying proprietary AI to Microeconomics & Finance to help institutional investors identify highly promising SMEs and accelerate their growth.We’re an ambitious, talented & international team of 30+ eager to build high-quality solutions with real impact on the economy & society.Backed by strong investors & strategic partners across the fintech sector, we build a suite of disruptive SaaS products using cutting-edge technology: AWS cloud-first architecture, Glue + Pyspark orchestration for Big Data, multi-agent AI systems on Amazon Bedrock, AI-accelerated development with Claude Code, modern stack (Spring Boot, React-Redux).The real challenge is execution: delivering fast without compromising quality.If you’re motivated by building mission-critical infrastructure that impacts million-dollar decisions, this is your place.We are looking for a Senior Data Engineer to lay the data foundations of a brand new product we are currently building.?? The roleBuild data pipelines: integrate diverse sources (HTML, CSV, relational databases, embeddings) using scalable ETLs.Modeling and optimization: design analytical models to generate KPIs and efficiently manage large data volumes.Enable AI: prepare datasets for ML, LLMs, and RAG systems, integrating AI for natural language queries.?DataOps and scalability: apply CI/CD, continuous monitoring, and optimize infrastructure.??Learn as much as you want about the world of alternative investment What we’re looking forResults-oriented with strong technical ownership.Around 3-4 years of experience.Relevant experience with SQL / PL-SQLRelevant experience with Python (pandas, Pyspark) and Apache sparkRelevant experience with ETLs & E/R modelsRelevant experience working with Data & Development teamsExperience with AWS services (EMR, Lambdas,…) or similar CloudFluency in Spanish and English? This gives extra pointsBasic experience with data science environmentsBasic experience with Vector database and with scraping enginesWork with multi-country and multi-source data.Experience working in with financial data What we offerBase pay + performance bonus, private health insurance, Gympass and pension plan 25 days of vacation (and your birthday off!) Hybrid mode: 2 days in office 3 days in remote Location: Downtown Madrid (Salamanca district) If interested, please email

??Learn as much as you want about the world of alternative investment What we’re looking forResults-oriented with strong technical ownership.Around 3-4 years of experience.Relevant experience with SQL / PL-SQLRelevant experience with Python (pandas, Pyspark) and Apache sparkRelevant experience with ETLs & E/R modelsRelevant experience working with Data & Development teamsExperience with AWS services (EMR, Lambdas,…) or similar CloudFluency in Spanish and English? This gives extra pointsBasic experience with data science environmentsBasic experience with Vector database and with scraping enginesWork with multi-country and multi-source data.Experience working in with financial data What we offerBase pay + performance bonus, private health insurance, Gympass and pension plan 25 days of vacation (and your birthday off!) Hybrid mode: 2 days in office 3 days in remote Location: Downtown Madrid (Salamanca district) If interested, please email

Salamanca, España

? About usmscope is a fast growing fintech applying proprietary AI to Microeconomics & Finance to help institutional investors identify highly promising SMEs and accelerate their growth. We’re an ambitious, talented & international team of 30+ eager to build high-quality solutions with real impact on the economy & society.Backed by strong investors & strategic partners across the fintech sector, we build a suite of disruptive SaaS products using cutting-edge technology: AWS cloud-first architecture, Glue + Pyspark orchestration for Big Data, multi-agent AI systems on Amazon Bedrock, AI-accelerated development with Claude Code, modern stack (Spring Boot, React-Redux). The real challenge is execution: delivering fast without compromising quality.