Data Engineer

Senovo IT Ltd; Madrid; Híbrido; EUR 40.000 - 60.000; Jornada completa

Descripción de la vacante

Senovo IT Ltd in Madrid is seeking a Junior/Medior Data Engineer to join an international data team. The role focuses on developing and maintaining data pipelines, ensuring reliability, quality, and performance across the data platform.

The position is hybrid (2 days in the office per week) and requires 2–4 years of experience, with strong Python, AWS, SQL, and Airflow skills, plus fluency in English and Spanish.

Formación

• 2–4 years of professional experience in Data Engineering.
• Strong Python development and data processing skills.
• Practical experience with AWS data services and SQL.
• Experience with data pipeline orchestration (Airflow) and ETL/ELT.
• Ability to operate in a hybrid Madrid-based setup.

Responsabilidades

• Develop, maintain, and improve data pipelines and ETL/ELT processes.
• Use Python for data processing and automation.
• Support orchestration and monitoring of workflows with Airflow.
• Work with AWS data services and cloud platforms.
• Ensure data quality checks and validation processes.
• Troubleshoot data pipeline issues and optimize performance.
• Collaborate in an international Data Engineering team using Agile methods.
• Document data workflows and development practices.

Conocimientos

Python

SQL

AWS

Airflow

Git

English communication

Spanish communication

Problem solving

Herramientas

Apache Airflow

AWS Cloud Services

Docker

dbt

Kafka

Spark / PySpark

Databricks

Redshift

S3

Lambda

Glue

Descripción del empleo

Work Model: Hybrid - 2 days per week in the office

Contract: 9 months+

Languages: Spanish and English

About the Role

We are looking for a Junior/Medior Data Engineer to join an international data engineering team based in Madrid.

The role will focus on supporting the development, maintenance, monitoring, and day-to-day operation of data pipelines and data processing workflows.

You will work closely with senior Data Engineers, contributing to the reliability, quality, performance, and continuous improvement of the data platform.

This is a hands-on position, ideally suited to someone with 2-4 years of professional experience in Data Engineering and practical experience with Python, AWS, SQL, and data pipeline orchestration technologies.

Key Responsibilities

• Develop, maintain, and improve data pipelines and ETL/ELT processes.
• Use Python for data processing, automation, and pipeline development.
• Support the orchestration and monitoring of workflows using Apache Airflow or similar tools.
• Work with AWS data services and cloud-based data platforms.
• Monitor existing pipelines and help investigate and resolve operational issues.
• Implement and maintain data quality checks and validation processes.
• Identify and resolve data inconsistencies, pipeline failures, and data processing issues.
• Support senior Data Engineers in developing and optimizing data workflows.
• Contribute to improving the reliability, performance, and maintainability of existing pipelines.
• Follow established practices for development, testing, version control, and deployment.
• Collaborate within an international Data Engineering team using Agile methodologies.
• Document technical processes and data workflows when required.
• 2-4 years of professional experience in Data Engineering or a closely related role.
• Strong practical experience with Python.
• Hands-on experience with AWS and AWS-based data environments.
• Experience with Apache Airflow or a similar data orchestration tool.
• Good understanding of ETL/ELT processes and data pipelines.
• Experience working with SQL and relational or cloud databases.
• Experience with data quality, validation, and data consistency checks.
• Ability to troubleshoot and resolve technical issues within data pipelines.
• Good understanding of software development fundamentals, including Git/version control.
• Good communication skills in both English and Spanish.
• Ability and willingness to work in a hybrid model from Madrid, 2 days per week in the office.

Desirable / Nice to Have

• Experience with Apache Spark / PySpark.
• Experience with AWS data services such as AWS Glue, S3, Lambda, Redshift, or similar.
• Knowledge of Docker / ECS.
• Experience with dbt.
• Familiarity with Databricks.
• Knowledge of Kafka or other data streaming technologies.
• Experience with data governance or advanced data quality frameworks.
• Familiarity with Agile / Scrum methodologies.
• Experience working with large-scale or international data environments.

What We're Looking For

A hands-on Data Engineer who is comfortable working with existing data pipelines, troubleshooting issues, improving processes, and collaborating with more senior engineers. The ideal candidate combines solid technical fundamentals with a practical, problem-solving mindset and strong communication skills.