Data Engineer - ETL, Airflow & Cloud Pipelines

Ampleshift

Lisboa

Presencial

EUR 45 000 - 65 000

Tempo integral

há 39 horas
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Resumo da oferta

Ampleshift, a consulting firm specializing in MuleSoft, Workato, Boomi, and other leading technologies, is seeking a Data Engineer in Lisbon to build and maintain scalable data pipelines. You will work with SQL, Python, ETL/ELT processes and Airflow, leveraging cloud data platforms (AWS/Azure/GCP) to design data models and uphold data quality standards.

Fluency in Portuguese and English is required. Bachelor's degree or equivalent experience; knowledge of Spark, dbt, Snowflake, BigQuery, or

Qualificações

  • 2+ years of experience as a Data Engineer, building and maintaining data pipelines.
  • Strong SQL skills and hands-on experience with Python.
  • Experience building ETL/ELT pipelines from source systems to data warehouses or lakes.
  • Experience with a pipeline orchestration tool (Airflow).
  • Familiarity with cloud data platforms (AWS, Azure, or GCP).
  • Understanding of data modeling and data quality practices.
  • Fluent in Portuguese and English (spoken and written).
  • Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent experience).

Conhecimentos

SQL
Python
ETL/ELT pipelines
Apache Airflow
Cloud data platforms (AWS/Azure/GCP)
Data modeling
Data quality
Portuguese language
English language

Formação académica

Bachelor's degree in Computer Science, Engineering, or related field

Ferramentas

dbt
Snowflake
BigQuery
Kafka

Descrição da oferta de emprego

Ampleshift, a consulting firm specializing in MuleSoft, Workato, Boomi, and other leading technologies, is seeking a Data Engineer in Lisbon to build and maintain scalable data pipelines. You will work with SQL, Python, ETL/ELT processes and Airflow, leveraging cloud data platforms (AWS/Azure/GCP) to design data models and uphold data quality standards.

Fluency in Portuguese and English is required. Bachelor's degree or equivalent experience; knowledge of Spark, dbt, Snowflake, BigQuery, or

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