Senior Data Engineer: Lake Modernization with AWS & Iceberg

ERNI; Madrid; Híbrido; EUR 60.000 - 90.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Certifications covered

Private health insurance

Sick leave coverage

Emotional support

Flexible remuneration

Referral bonuses

Vacation days

Language courses

Descripción de la vacante

ERNI is seeking a senior Data Engineer to accelerate a data platform modernization in Madrid, working with AWS services (S3, Athena, Redshift, Lambda), Apache Iceberg, Python, SQL, and DuckDB to improve scalability and governance.

You will collaborate with a team, mentor others, and contribute to a cloud-native data ecosystem while enjoying a hybrid work model and strong support from the ERNI community.

Formación

• 4 to 6+ years of experience in Data Engineering and cloud-native data platforms.
• Hands-on experience with AWS services such as S3, Athena, Redshift and Lambda.
• Experience working with Apache Iceberg, Delta Lake or Hudi and strong knowledge of data modeling, partitioning and schema evolution.
• Proficiency in Python, SQL, DuckDB or similar transformation technologies and Docker.
• Experience with Git and performance optimization of analytical workloads.

Responsabilidades

• Migrate datasets and pipelines to an Apache Iceberg architecture.
• Develop Python-based data processing jobs and SQL transformations with DuckDB.
• Optimize performance and cost efficiency, manage Redshift data structures and views.
• Participate in testing and code reviews, and ensure documentation and knowledge transfer across the project.

Conocimientos

AWS S3

Athena

Redshift

Iceberg

Python

SQL

DuckDB

Git

Performance optimization

Herramientas

Docker

Descripción del empleo

ERNI is seeking a senior Data Engineer to accelerate a data platform modernization in Madrid, working with AWS services (S3, Athena, Redshift, Lambda), Apache Iceberg, Python, SQL, and DuckDB to improve scalability and governance.

You will collaborate with a team, mentor others, and contribute to a cloud-native data ecosystem while enjoying a hybrid work model and strong support from the ERNI community.