Data Engineer: Build Data Products with dbt & Databricks

PostNL

Den Haag

Híbrido

EUR 51 000 - 73 000

Tempo integral

Há 6 dias
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Currículo e carta de apresentação personalizados, prontos a enviar.

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Vantagens oferecidas por esta oferta de emprego

Hybrid working
Flexible working hours
Laptop and smartphone
Pension plan
Training opportunities

Resumo da oferta

PostNL is looking for a Data Engineer to power data products across the IT for IT domain in the Netherlands. You will contribute to dashboards, analyses and algorithms by delivering reliable data assets.

You will build ELT/ETL pipelines, shape data models and drive the transition toward dbt and Databricks, while collaborating with multiple teams. Hybrid work and development opportunities are offered.

Qualificações

  • A higher vocational or university degree relevant to data engineering.
  • 5+ years of experience as a Data Engineer or in a similar role.
  • Strong SQL skills and experience designing reusable data products using dimensional modelling.
  • Hands-on experience with dbt and/or Databricks and building ELT/ETL pipelines in production environments.
  • Experience with cloud platforms, CI/CD and Infrastructure as Code, preferably within AWS environments.

Responsabilidades

  • Design, build and maintain the data products that support the IT for IT domain.
  • Take ownership of data from ingestion to delivery and ensure reliability and reusability.
  • Build ELT/ETL pipelines and develop scalable data models.
  • Collaborate with the central data platform team on standards, governance and architecture.

Conhecimentos

SQL
Data modeling
ETL/ELT
dbt
Databricks

Formação académica

Bachelor's or higher in data engineering

Ferramentas

AWS
CI/CD
Infrastructure as Code
Databricks
dbt

Descrição da oferta de emprego

PostNL is looking for a Data Engineer to power data products across the IT for IT domain in the Netherlands. You will contribute to dashboards, analyses and algorithms by delivering reliable data assets.

You will build ELT/ETL pipelines, shape data models and drive the transition toward dbt and Databricks, while collaborating with multiple teams. Hybrid work and development opportunities are offered.

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