Data Engineer: Build Scalable Pipelines for Healthcare

BGBx

Lisboa

Presencial

EUR 60 000 - 75 000

Tempo integral

Há 8 dias

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Envia um currículo específico para a oferta em poucos minutos.

Vantagens oferecidas por esta oferta de emprego

Health insurance
Retirement plans
Paid time off
Learning & development
Wellness benefits

Resumo da oferta

BGBx in Lisbon, Portugal is seeking a Data Engineer with 3-5 years of experience to design, build, and maintain data pipelines that turn internal and external data into reliable datasets for analysis and downstream applications.

You will work with Python and SQL, modern cloud data technologies, and collaborate with analysts, data scientists, and product teams to ensure scalable, high-quality data solutions.

Qualificações

  • 3–5 years hands-on data engineering experience building and maintaining data pipelines.
  • Strong Python and SQL skills.
  • Experience with at least one cloud data warehouse (e.g., BigQuery, Redshift, Snowflake).
  • Familiarity with orchestration tools (Airflow, Dagster, Prefect, Flyte).
  • Cloud platform experience with GCP, AWS, or Azure.
  • Strong DB knowledge and problem-solving skills.

Responsabilidades

  • Design, build, and maintain ETL/ELT data pipelines.
  • Extract, clean, transform, and model data from internal and external sources.
  • Develop data solutions using Python and SQL.
  • Work with large-scale datasets and cloud-based data infrastructure.
  • Support data consumers, including analysts and data scientists.
  • Monitor pipeline health, troubleshoot failures, and optimize performance.

Conhecimentos

Data engineering experience
Python
SQL
Cloud data warehousing
Orchestration tools
Cloud platforms

Descrição da oferta de emprego

BGBx in Lisbon, Portugal is seeking a Data Engineer with 3-5 years of experience to design, build, and maintain data pipelines that turn internal and external data into reliable datasets for analysis and downstream applications.

You will work with Python and SQL, modern cloud data technologies, and collaborate with analysts, data scientists, and product teams to ensure scalable, high-quality data solutions.

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