Senior Data Engineer — Hybrid Madrid, SQL + BI Pipelines

EPAM Systems; España; Hybrid; PHP 5,095,000 - 8,006,000; Full time

Job summary

EPAM Systems in Madrid, Spain, seeks a Senior Data Engineer (Python/Tableau) to join our hybrid team. You will design and optimize SQL-driven data transformations, develop scalable ETL/ELT pipelines and support analytics, financial and regulatory reporting.

Collaborate with cross-functional teams to deliver clean datasets, implement data quality checks, and extend enterprise data models (Data Vault, dimensional, 3NF).

Qualifications

• Bachelor’s or Master’s degree in CS, IS, or related field.
• 5+ years of experience with SQL-centric data engineering or backend roles.
• Expert-level SQL development including query optimization and tuning.
• Strong data modeling knowledge: Data Vault, dimensional, SCD, 3NF.
• Hands-on Python for automation and integration tasks.
• Experience with Tableau or Power BI for BI enablement.
• Banking or financial domain experience is desirable.
• Excellent problem-solving and stakeholder collaboration.

Responsibilities

• Develop and optimize SQL transformations to support analytics and reporting.
• Design and extend enterprise data models (Data Vault, dimensional, 3NF).
• Build and operate SQL-driven ETL/ELT pipelines with reliability.
• Use Python for automation, API integrations and workflow enhancements.
• Prepare datasets for BI tools like Tableau and Power BI.
• Ensure monitoring, observability and production stability of pipelines.
• Collaborate with finance, risk and compliance stakeholders.

Skills

SQL development

Python

Tableau

Power BI

Data modelling

Data quality

CI/CD

Stakeholder collaboration

English communication

Education

Bachelor's/Master's degree in CS/IS

Job description

EPAM Systems in Madrid, Spain, seeks a Senior Data Engineer (Python/Tableau) to join our hybrid team. You will design and optimize SQL-driven data transformations, develop scalable ETL/ELT pipelines and support analytics, financial and regulatory reporting.

Collaborate with cross-functional teams to deliver clean datasets, implement data quality checks, and extend enterprise data models (Data Vault, dimensional, 3NF).