Senior Data Engineer — Cloud Data Lakehouse & AI Pipelines

AstraZeneca; Barcelona; Presencial; EUR 90.000 - 120.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health and travel insurance

Annual leave

Reduced-hours timetable

Retirement plan

Descripción de la vacante

AstraZeneca’s Evinova team in Barcelona is seeking a Senior Data Engineer to design and automate our data foundation, enabling product, data science and agents to deliver advanced capabilities.

You will work hands-on with cloud data tools, drive lakehouse architectures, and mentor peers while collaborating across IT, product management and security to ensure reliable data products and scalable pipelines.

Formación

• 7+ years of hands-on data engineering experience, preferably in SaaS/multi-tenant environments.
• Strong cloud experience with AWS data services, security and governance.
• Experience designing data lakehouse architectures, ETL pipelines and data modeling.

Responsabilidades

• Infrastructure design and management using AWS data services (Lake Formation, Glue, Athena, EMR/Redshift).
• Work with open table formats (Iceberg/Delta Lake) and manage schema/partition evolution.
• Build and operate streaming pipelines (Kinesis/MSK) with exactly-once semantics and windowing.
• Define infrastructure as code using AWS CDK or CloudFormation.
• Maintain CI/CD for data pipelines (GitHub Actions; Terraform).
• Model data, design dimensional schemas and governance policies.
• Develop ETL logic using Python or Spark; validate data quality.
• Mentor junior engineers and collaborate with product, security and other teams.

Conocimientos

AWS

Data engineering

PySpark

SQL

Python

Kubernetes

CI/CD

Glue

Athena

Kinesis

Herramientas

Docker

Airflow

Terraform

GitHub Actions

Descripción del empleo

AstraZeneca’s Evinova team in Barcelona is seeking a Senior Data Engineer to design and automate our data foundation, enabling product, data science and agents to deliver advanced capabilities.

You will work hands-on with cloud data tools, drive lakehouse architectures, and mentor peers while collaborating across IT, product management and security to ensure reliable data products and scalable pipelines.