ML Data Engineer: Cloud Pipelines & Production

NielsenIQ; Madrid; Presencial; EUR 38.000 - 55.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Flexible working environment

Volunteer time off

Descripción de la vacante

NIQ is seeking an experienced Data Engineer to join our growing Machine Learning team in Madrid, Spain. You'll build and maintain data infrastructure powering ML workflows, from raw data ingestion to model deployment.

Responsibilities include designing data pipelines, deploying flows in orchestration tools, improving CI/CD, and ensuring data quality across distributed cloud environments using GCP services. Collaboration with data scientists is essential for scalable ML delivery.

Formación

• 3–5 years of experience as a Data Engineer.
• Strong proficiency in Python.
• Experience with distributed systems for big data processing (Dask, Spark).
• Experience building ETL pipelines and CI/CD.
• Hands-on experience with GCP core data services (BigQuery, Cloud Storage, Cloud Build, GKE).
• Experience with orchestration tools (Airflow, Dagster, or similar).
• Comfortable working in a Linux environment with Jupyter, Python, Git, Docker, SQL, and NoSQL.
• Strong experience with Pandas, SQL, and writing Dockerfiles.

Responsabilidades

• Design and build data pipelines/flows for ML use cases
• Deploy and manage flows in orchestration tools
• Improve and maintain CI/CD pipelines
• Deploy data scientists' scripts and models from notebooks to production
• Implement data quality checks to ensure pipeline reliability
• Optimize data processing jobs for performance and cost, particularly on distributed systems and cloud data services

Conocimientos

Python

Pandas

SQL

NoSQL

Linux

Jupyter

Git

Docker

Dockerfiles

Airflow

Dagster

Spark

Dask

BigQuery

Cloud Storage

Cloud Build

GKE

Herramientas

Docker

Airflow

Dagster

Spark

Dask

BigQuery

Cloud Storage

Cloud Build

GKE

Descripción del empleo

NIQ is seeking an experienced Data Engineer to join our growing Machine Learning team in Madrid, Spain. You'll build and maintain data infrastructure powering ML workflows, from raw data ingestion to model deployment.

Responsibilities include designing data pipelines, deploying flows in orchestration tools, improving CI/CD, and ensuring data quality across distributed cloud environments using GCP services. Collaboration with data scientists is essential for scalable ML delivery.