Senior Data Engineer, Madrid

Senior Data EngineerAre you a forward-thinking professional with a strong background in Data Engineering and an interest in financial services?Join as a Senior Data Engineer and help build and evolve enterprise data ecosystems for customers.Design scalable data pipelines, ensure high-quality data flows and integrate complex APIs while collaborating with cross-functional teams to deliver robust and reliable data products.This is a hybrid role based in Madrids city center, ideal for those eager to thrive in a dynamic environment and make a significant impact in private banking technology.Join EPAM and contribute to shaping the future of financial services in Spain!Responsibilities - Design, build and optimize scalable Python-based ETL/ELT pipelines using frameworks such as pandas or Polars - Orchestrate data pipelines using Dagster, Airflow or similar tools - Develop efficient data ingestion pipelines for batch, incremental and streaming scenarios - Integrate with internal and external APIs ensuring robust authentication, error handling and data quality - Implement best-in-class data models including dimensional modelling and domain-driven structures - Manage application lifecycle and reduce architecture debt - Deploy, operate and monitor data pipelines using Docker, Kubernetes and GitLab - Develop and maintain CI/CD pipelines for data workflows and infrastructure components - Collaborate with data scientists, software engineers and platform teams to enhance data services and deployment processes - Support troubleshooting, incident response and participate in architecture discussions Requirements - Bachelors or Masters degree in Computer Science, Engineering, Data Science or related field - Minimum 5 years of experience in data engineering or backend engineering with a strong data focus - Expert-level Python skills with frameworks such as pandas or Polars - Experience with data orchestration frameworks (Dagster, Airflow or similar) - Strong understanding of data modelling, ETL patterns and performance considerations - Proficiency with Docker, Kubernetes and GitLab CI/CD - Hands-on experience with SQL and relational databases (MS SQL preferred) - Practical experience with Azure data and compute services or comparable AWS/GCP experience - Passion for building robust, maintainable and well-tested data systems - Strong focus on scalability, reliability, data quality and monitoring Nice to have - Experience in regulated environments such as finance, insurance or healthcare - Certifications in cloud, Kubernetes or DevOps (CKA, AWS/GCP/Azure) - Familiarity with distributed systems, microservices and API-driven architectures - Commitment to automation, reproducibility and DevOps practices - Creativity and new ideas to enhance the platform - Ability to work under pressure and tough deadlines - Strong communication skills and product-thinking mindset - Comfortable working in agile environments - Fluency in Spanish Python, pandas, Polars, Dagster, Airflow, Docker, ETL

Senior Data EngineerAre you a forward-thinking professional with a strong background in Data Engineering and an interest in financial services? Join as a Senior Data Engineer and help build and evolve enterprise data ecosystems for customers. Design scalable data pipelines, ensure high-quality data flows and integrate complex APIs while collaborating with cross-functional teams to deliver robust and reliable data products., Science, Engineering, Data Science or related field, Minimum 5 years of experience in data engineering or backend engineering with a strong data focus - Expert-level Python skills with frameworks such as pandas or Polars - Experience with data orchestration frameworks (Dagster, Airflow or similar) - Strong understanding of data modelling, ETL patterns and performance considerations - Proficiency with Docker, Kubernetes and GitLab CI/CD - Hands-on experience with SQL and relational databases (MS SQL preferred) - Practical experience with Azure data and compute services or comparable AWS/GCP experience - Passion for building robust, maintainable and well-tested data systems - Strong focus on scalability, reliability, data quality and monitoring Nice to have - Experience in regulated environments such as finance, insurance or healthcare - Certifications in cloud, Kubernetes or DevOps (CKA, AWS/GCP/Azure) - Familiarity with distributed systems, microservices and API-driven architectures - Commitment to automation, reproducibility and DevOps practices - Creativity and new ideas to enhance the platform - Ability to work under pressure and tough deadlines - Strong communication skills and product-thinking mindset - Comfortable working in agile environments - Fluency in Spanish Python, pandas, Polars, Dagster, Airflow, Docker, ETL