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2 дня назад

Data Engineer (AI/ML)

38 400 - 55 000
Тип работы
fulltime
Грейд
middle
Английский
c1
Страна
Spain
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Data Engineer (AI/ML) (Python, GCP): Building and maintaining data infrastructure and pipelines that power machine learning workflows, from raw data ingestion through model deployment, with an accent on distributed processing, orchestration, and data quality. Focus on deploying notebook-based models to production, optimizing cloud data jobs for performance and cost, and improving CI/CD reliability.

Location: Madrid, Spain

Salary: EUR 38,400–55,000 yearly

Company

NIQ is a publicly traded consumer intelligence company providing retail and consumer buying insights through advanced analytics and data platforms.

What you will do

  • Design and build data pipelines and flows for machine learning use cases.
  • Implement data versioning, quality checks, and reliable pipeline practices.
  • Deploy and manage workflows using orchestration tools such as Airflow or Dagster.
  • Deploy data scientists’ scripts and models from notebooks to production.
  • Improve CI/CD pipelines and manage Python dependencies with Poetry and uv.
  • Optimize distributed data processing jobs for performance and cloud cost.

Requirements

  • 3–5 years of experience as a Data Engineer.
  • Strong Python, Pandas, SQL, and Dockerfile development skills.
  • Experience with ETL pipelines and distributed systems such as Dask or Spark.
  • Hands-on experience with GCP data services, including Cloud Storage, BigQuery, Cloud Build, and GKE.
  • Experience with orchestration tools and Linux environments using Jupyter, Git, Docker, SQL, and NoSQL.
  • Professional-level English.

Nice to have

  • Experience working with machine learning datasets and building pipelines for AI models.
  • Experience with LangGraph and retrieval-augmented generation systems.

Culture & Benefits

  • Flexible working environment.
  • Volunteer time off.
  • LinkedIn Learning access.
  • Employee Assistance Program.

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