Senior Data Engineer (Madrid) - €60.000 - €85.000 A Year
Senior Data Engineer at an AI fintech in Madrid (hybrid, on-site 2-3 days/week), building and maintaining end-to-end data ingestion and ETL pipelines, writing production Python and SQL, orchestrating with Kubernetes, and designing schemas and transformation layers for analytics and RAG systems on Azure/AWS.
- Compensation
- €60K–€85K / yr
- Location
- Madrid, Spain
- Work setup
- Hybrid
- Seniority
- Senior
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Strong Python (advanced, production-ready)
- Advanced SQL
- ETL/ELT pipeline design and orchestration (Airflow, ADF, Databricks, or similar)
- Experience with RAG systems, embeddings, and vector databases
- Hands-on experience with cloud systems: Azure, AWS
- API and database integration
- Experience with Kubernetes and workflow tools for orchestration
Nice to have
- Experience with Snowflake and Oracle
- Data Lakehouse architectures
- LLM evaluation and prompt engineering
- Experience building AI or data platforms
Full description
I am looking for a Senior Data Engineer with strong Python experience and a strong understanding with RAG systems for an exciting AI Fintech.
Todos los candidatos deben asegurarse de leer atentamente la siguiente descripción del puesto y la información antes de enviar su solicitud.
This role is a hybrid position based in Madrid, Spain where you will be expected to collaborate 2-3 days a week. For this position, you can be expected to be paid in the region of €60-€85,000 plus benefits.
As the Senior Data Engineer for this role, you will be responsible for building and maintaining end-to-end data ingestion and ETL pipelines. Ingest structured and unstructured data from a variety of sources and market data providers, using Kubernetes and other workflow tools to orchestrate. Develop high-quality Python code and data flows. xhfqzwm Any experience in designing schemas and transformation layers for analytics and AI agents/RAG systems.
Qualifications
Strong Python (advanced, production‑ready)
Advanced SQL
ETL/ELT pipeline design and orchestration (Airflow, ADF, Databricks, or similar)
Experience with RAG systems, embeddings, and vector databases
Hands‑on experience with cloud systems: Azure, AWS
API and database integration
Nice‑to‑Have
Experience with Snowflake and Oracle
Data Lakehouse architectures
LLM evaluation and prompt engineering
Experience building AI or data platforms