We're looking for a Senior Data Engineer (Python/Tableau) to join our team in Madrid, Spain in a hybrid working mode. In this role, you will design and optimize SQL-driven data transformations, develop scalable ETL/ELT pipelines, and contribute to enterprise data models supporting analytical, financial and regulatory reporting. This position provides an opportunity to work in a dynamic financial environment, partnering with cross-functional teams to deliver clean, reliable datasets while leveraging automation, BI optimization and engineering best practices for high-impact business intelligence enablement.
Responsibilities

Develop and optimize complex SQL transformations to support analytics and reporting
Design and extend enterprise data models (Data Vault, dimensional, 3NF) and maintain standards
Implement data quality checks, validation logic and SQL testing frameworks
Build and operate SQL-centric ETL/ELT pipelines, applying optimization and reliability principles
Use Python for automation, API integrations and workflow enhancement




Structure datasets for consumption in BI tools (Tableau, Power BI), assisting with performance and governance
Partner with business stakeholders in finance, risk and compliance to translate requirements into data solutions
Ensure monitoring, observability and operational stability of pipelines in production environments
Follow engineering best practices including version control, documentation and CI/CD integration
Contribute to platform improvement, performance tuning, and architectural roadmap initiatives
Requirements

Bachelor’s/Master’s degree in Computer Science, Information Systems or related field
Minimum 5+ years of experience in SQL-centric data engineering or backend roles
Expert-level experience in SQL development including query optimization and tuning
Strong background in data modelling techniques: Data Vault, dimensional, SCD and 3NF
Hands-on experience in building SQL-driven transformations and scalable data solutions
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📌 Senior Data Engineer (Madrid)
🏢 Epam Systems
📍 Madrid