Data Engineer

About us mscope is a applying to Microeconomics & Finance to help institutional investors identify highly promising SMEs and accelerate their growth.We’re an ambitious, talented & international team of + 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 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 , modern stack (Spring Boot, React-Redux).The real challenge is execution: delivering fast without compromising quality.If you’re motivated by building - that impacts - , this is your place.We are looking for a to lay the data foundations of a brand new product we are currently building.? The role Build 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 for Results-oriented with strong technical ownership.Around 3-4 years of experience.Relevant experience with SQL / PL-SQL Relevant experience with Python (pandas, Pyspark) and Apache spark Relevant experience with ETLs & E/R models Relevant experience working with Data & Development teams Experience with AWS services (EMR, Lambdas,…) or similar Cloud Fluency in Spanish and English ? This gives extra points Basic experience with data science environments Basic experience with Vector database and with scraping engines Work with multi-country and multi-source data.Experience working in with financial data What we offer Base pay + , 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 **

Relevant experience with SQL / PL-SQL Relevant experience with Python (pandas, Pyspark) and Apache spark Relevant experience with ETLs & E/R models Relevant experience working with Data & Development teams Experience with AWS services (EMR, Lambdas,…) or similar Cloud Fluency in Spanish and English ? This gives extra points Basic experience with data science environments Basic experience with Vector database and with scraping engines Work with multi-country and multi-source data. Experience working in with financial data What we offer Base pay + , 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 **

About us mscope is a applying to Microeconomics & Finance to help institutional investors identify highly promising SMEs and accelerate their growth. We’re an ambitious, talented & international team of + 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 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 , modern stack (Spring Boot, React-Redux). The real challenge is execution: delivering fast without compromising quality. If you’re motivated by building - that impacts - , this is your place. We are looking for a to lay the data foundations of a brand new product we are currently building. ? The role Build 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 for Results-oriented with strong technical ownership.