Senior Data Engineer
Summary
Senior Data Engineer builds and scales Python ETL/ELT pipelines and APIs to power private banking data products in Madrid.
Experteer Overview
Por favor, lea detenidamente la información de esta oferta de empleo para entender exactamente qué se espera de los posibles candidatos.
As a Senior Data Engineer at EPAM in Madrid, you will design and evolve scalable data ecosystems for private banking clients. You will build Python-based ETL/ELT pipelines and integrate complex APIs, collaborating with cross-functional teams to deliver reliable data products. You’ll tackle data ingestion for batch, incremental, and streaming scenarios while ensuring data quality and robust authentication. This hybrid role offers a chance to impact financial services in Spain by shaping data-powered solutions at scale.
Compensaciones / Beneficios
• Design, build and optimize scalable Python ETL/ELT pipelines using pandas or Polars
• Orchestrate data workflows with Dagster, Airflow or similar tools
• Develop data ingestion pipelines for batch, incremental and streaming data
• Integrate with internal and external APIs with robust authentication and error handling
• Implement dimensional modeling and domain-driven data structures
• Manage application lifecycle and reduce architecture debt
• Deploy, operate and monitor pipelines with Docker, Kubernetes and GitLab
• Develop and maintain CI/CD pipelines for data workflows and infrastructure
• Collaborate with data scientists, software engineers and platform teams to enhance data services
• Support troubleshooting, incident response and participate in architecture discussions
Responsabilidades
• Strong experience in data engineering and building data ecosystems
• Proficiency in Python-based ETL/ELT development xqbhyrx
• Experience with data orchestration tools (Dagster, Airflow)
• Knowledge of data ingestion for batch, incremental and streaming data
• API integration with secure authentication and data quality focus
• Experience with data modeling (dimensional, domain-driven)
• Familiarity with containerization and orchestration (Docker, Kubernetes) and GitLab
• CI/CD for data workflows and infrastructure
• Cross-functional collaboration and problem-solving ability
Requisitos principales
•
Por favor, lea detenidamente la información de esta oferta de empleo para entender exactamente qué se espera de los posibles candidatos.
As a Senior Data Engineer at EPAM in Madrid, you will design and evolve scalable data ecosystems for private banking clients. You will build Python-based ETL/ELT pipelines and integrate complex APIs, collaborating with cross-functional teams to deliver reliable data products. You’ll tackle data ingestion for batch, incremental, and streaming scenarios while ensuring data quality and robust authentication. This hybrid role offers a chance to impact financial services in Spain by shaping data-powered solutions at scale.
Compensaciones / Beneficios
• Design, build and optimize scalable Python ETL/ELT pipelines using pandas or Polars
• Orchestrate data workflows with Dagster, Airflow or similar tools
• Develop data ingestion pipelines for batch, incremental and streaming data
• Integrate with internal and external APIs with robust authentication and error handling
• Implement dimensional modeling and domain-driven data structures
• Manage application lifecycle and reduce architecture debt
• Deploy, operate and monitor pipelines with Docker, Kubernetes and GitLab
• Develop and maintain CI/CD pipelines for data workflows and infrastructure
• Collaborate with data scientists, software engineers and platform teams to enhance data services
• Support troubleshooting, incident response and participate in architecture discussions
Responsabilidades
• Strong experience in data engineering and building data ecosystems
• Proficiency in Python-based ETL/ELT development xqbhyrx
• Experience with data orchestration tools (Dagster, Airflow)
• Knowledge of data ingestion for batch, incremental and streaming data
• API integration with secure authentication and data quality focus
• Experience with data modeling (dimensional, domain-driven)
• Familiarity with containerization and orchestration (Docker, Kubernetes) and GitLab
• CI/CD for data workflows and infrastructure
• Cross-functional collaboration and problem-solving ability
Requisitos principales
•