Senior Data Engineer

Job Description: Senior Data Engineer (SDE) – Madrid

Experience: 5+ Years (with strong specialization in Big Data & Cloud Data Platforms)

Location: Madrid

Work Type - Remote with once a week travel to Madrid

The Opportunity

As a Senior Data Engineer (SDE) at Celebal Technologies, you will play a key role in delivering scalable, high-performance data solutions for global clients.

This is a hands-on role focused on building, optimizing, and maintaining modern data systems. You will work across the full data lifecycle—from ingestion to analytics—while ensuring reliability, scalability, and efficiency.

What You Will Do (Key Responsibilities)

Data Engineering & Pipelines

• Build and maintain scalable batch and streaming data pipelines
• Develop robust workflows for data ingestion, transformation, and validation

Production Support & Optimization

• Troubleshoot and resolve production issues in data pipelines
• Optimize performance and ensure system reliability

Architecture & Design

• Contribute to data architecture design and implementation
• Support migration and modernization of legacy data systems

Data Quality & Governance

• Implement data validation, monitoring, and governance practices
• Ensure compliance with data security and privacy standards

Cloud & Platform Integration

• Work with cloud platforms (AWS / Azure / GCP)
• Integrate data systems with cloud storage and services

DevOps & Automation

• Support CI/CD pipelines and automated deployments
• Contribute to improving operational efficiency and monitoring

Collaboration & Delivery

• Work with cross-functional teams to deliver end-to-end data solutions
• Support client requirements and ensure timely delivery

The Ideal Profile (Must-Have Skills)

Experience

• 5+ years of experience in:
• Data Engineering
• Data Warehousing & Analytics
• Big Data and distributed systems

Programming

• Strong skills in Python and SQL
• Experience with PySpark
• Familiarity with version control (Git)

Cloud & Data Platforms

• Experience with AWS / Azure / GCP
• Understanding of data lakes and distributed processing systems

Data Modeling & Pipelines

• Experience with ETL/ELT pipelines and data modeling techniques
• Knowledge of batch and streaming architectures

Nice-to-Have Skills

• Familiarity with modern data warehousing platforms
• Experience with data quality and monitoring frameworks
• Exposure to ML/AI pipelines
• Experience with support and ticketing tools (JIRA, ServiceNow)
• Relevant certifications in data engineering or cloud technologies