Chief Cloud Architect

beBeeDataEngineer; Gijón; Presencial; EUR 50.000 - 70.000; Jornada completa

Descripción de la vacante

A global technology company seeks a Senior Data Engineer to join their international team in Gijón, Spain. The ideal candidate will lead projects utilizing cloud platforms like AWS or Azure and big data technologies like Spark and Hadoop to support advanced analytics. A minimum of 6 years of experience with strong skills in Python and SQL is required. This role emphasizes data quality, governance, and integration of machine learning models.

Formación

• 6 years of experience in data engineering.
• Proficient in producing cloud-based solutions with modern technologies.
• Experience embedding machine learning models.

Responsabilidades

• Work with cloud and big data technologies for advanced analytics.
• Ensure high data quality, governance, and performance.
• Collaborate within an international team.

Conocimientos

Advanced Python

SQL

Java

Scala

AWS

Azure

Spark

Hadoop

Kafka

Apache Airflow

Power BI

Tableau

Docker

Kubernetes

Descripción del empleo

Senior Data Engineer

Take your career to the next level with this exciting opportunity as a Senior Data Engineer. Be part of an international team and thrive in a global group with a diverse range of clients worldwide, and an agile environment.

The ideal candidate will work with modern cloud and big data technologies to support advanced analytics and machine learning integration. Your role will be key in ensuring high data quality, governance, and performance to drive business impact.

WHAT WOULD YOU NEED?

• 6 years of experience.
• Languages : Advanced Python and SQL; working experience with Java or Scala.
• Cloud Platforms : Proficiency with AWS or Azure (e.g., S3, Lambda, Redshift, ADF, Synapse).
• Big Data Technologies : Hands-on with Spark, Hadoop, Kafka.
• ETL / Workflow Tools : Experience with Apache Airflow, Talend, or similar.
• Databases : Strong experience with relational, NoSQL, and data warehouse systems (e.g., Snowflake, BigQuery).
• Machine Learning Integration : Experience embedding ML models using frameworks like TensorFlow, Scikit-learn, or PyTorch.
• DevOps : Knowledge of containerization (Docker, Kubernetes) and CI / CD tools (e.g., Jenkins, GitLab CI).
• Visualization : Proficient in Power BI or Tableau for dashboarding and reporting.
• Data Governance : Understanding of security, compliance (e.g., GDPR), and best practices in data handling.