Senior Data Engineer

EPAM Systems; España; On-site; PHP 4,926,108 - 6,773,398; Full time

Job summary

EPAM Systems is seeking a Senior Data Engineer to join our team in the Philippines. This hybrid role involves designing scalable data pipelines and integrating complex APIs to deliver robust financial data products.

As part of a dynamic environment, you'd work closely with cross-functional teams to enhance data services. A Bachelor's or Master's degree and a minimum of 5 years' experience in data engineering are required, along with expert-level Python skills.

Qualifications

• 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.
• Proficiency with Docker, Kubernetes and GitLab CI/CD.

Responsibilities

• Design, build and optimize scalable Python-based ETL/ELT pipelines.
• Develop and maintain CI/CD pipelines for data workflows.
• Collaborate with data scientists, software engineers and platform teams.

Skills

Python

Data Engineering

ETL/ELT processes

SQL

Docker

Kubernetes

Data Modelling

APIs Integration

Education

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science or related field

Tools

pandas

Polars

Dagster

Airflow

Azure data and compute services

MS SQL

Job description

Are 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 Madrid's 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.

Qualifications

• Bachelor’s or Master’s 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.
• Nice to have: Certifications in cloud, Kubernetes or DevOps (CKA, AWS/GCP/Azure).
• Nice to have: Familiarity with distributed systems, microservices and API-driven architectures.
• Nice to have: Commitment to automation, reproducibility and DevOps practices.
• Nice to have: Creativity and new ideas to enhance the platform.
• Nice to have: Ability to work under pressure and tough deadlines.
• Nice to have: Strong communication skills and product-thinking mindset.
• Nice to have: Comfortable working in agile environments.
• Nice to have: Fluency in Spanish.