Senior Data Engineer - Analytics Platform & Data Pipelines

super

España

Presencial

EUR 60.000 - 90.000

Jornada completa

Hace 5 días
Sé de los primeros/as/es en solicitar esta vacante
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Ventajas ofrecidas por este puesto de trabajo

Medical / Health Insurance
Open Annual Leave
Employee Assistance Programme
Training & Learning Development

Descripción de la vacante

Super is building a global analytics platform powering data-driven entertainment experiences. We are hiring a Senior Data Engineer to design, build, and scale ETL/ELT pipelines, models, and analytical layers that enable self‑serve analytics across Europe.

You will own end‑to‑end data initiatives, ensure data quality and observability, orchestrate workflows with Airflow or Dagster, and collaborate with product, analytics, and engineering teams to deliver trusted data solutions at scale.

Formación

  • Proven ability to design and build scalable ETL/ELT pipelines for high‑volume data.
  • Strong SQL and Python skills with production data pipelines and models.
  • Deep understanding of dimensional modelling and modern data warehousing.

Responsabilidades

  • Design, build, and evolve scalable ETL/ELT pipelines for high‑volume datasets.
  • Own medium‑to‑large data initiatives end‑to‑end from design to production.
  • Model analytics‑ready data using warehouse methodologies (Kimball, Inmon).
  • Develop and maintain curated analytical layers and data marts for self‑service analytics.
  • Orchestrate robust workflows using Airflow and similar tools; improve reliability.

Conocimientos

SQL
Python
Data modeling

Herramientas

Airflow
Dagster
Snowflake
BigQuery

Descripción del empleo

Super is building a global analytics platform powering data-driven entertainment experiences. We are hiring a Senior Data Engineer to design, build, and scale ETL/ELT pipelines, models, and analytical layers that enable self‑serve analytics across Europe.

You will own end‑to‑end data initiatives, ensure data quality and observability, orchestrate workflows with Airflow or Dagster, and collaborate with product, analytics, and engineering teams to deliver trusted data solutions at scale.

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