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Stefanini LATAM
Stefanini LATAM
ConsultingLogisticsMarketing
Stefanini LATAM is a technology solutions provider focused on digital transformation and business modernization. With more than 30 years of experience, the company helps organizations improve operational models and customer experiences through automation, artificial intelligence, cybersecurity, and data analytics. Its work combines consulting with technology implementation, supporting clients as they identify opportunities to optimize processes, respond to changing market conditions, and pursue sustainable growth.
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Junior Data Engineer

Join Stefanini LATAM as a Junior Data Engineer developing ETL and ELT pipelines on Google Cloud. Work with Python, SQL, Spark, BigQuery, and Airflow to build cloud data solutions.

CLChileHybridFull-timeJuniorNo degree requiredSpanish RequiredData Engineer
AirflowApacheBigQueryCloudETLGoogle Cloud PlatformHadoopKafkaNoSQLPySparkPythonSparkSQLTerraform

Description

  • Design, develop, and maintain batch and event-driven ETL and ELT data pipelines
  • Implement data processing and storage solutions on Google Cloud Platform
  • Build data processes with Python, SQL, and Spark or PySpark
  • Work with BigQuery, Cloud Storage, Dataflow, Dataproc, and Pub/Sub
  • Implement and maintain orchestration workflows with Airflow and Cloud Composer
  • Contribute to the development and evolution of Data Lake, Data Warehouse, and/or Lakehouse architectures
  • Design and optimize data models for information processing and analytics
  • Automate processes and deployments through CI/CD and Infrastructure as Code practices, preferably with Terraform
  • Establish controls for data quality, integrity, traceability, and availability
  • Optimize pipelines, queries, and processes for performance, scalability, and efficient resource use
  • Contribute to cloud data platform migrations and modernization initiatives
  • Collaborate with Architecture, Data Science, BI, Development, and business teams
  • Document implemented architectures, pipelines, models, and solutions
  • Provide technical support to the team and promote data engineering best practices

Requirements

  • Knowledge of Google Cloud Platform (GCP)
  • Experience with or knowledge of BigQuery, Cloud Storage, Dataflow and/or Dataproc, Pub/Sub, Python, advanced SQL, and Apache Spark or PySpark
  • Experience developing ETL and ELT pipelines
  • Knowledge of data modeling and transformation
  • Knowledge of Airflow or Cloud Composer for orchestration
  • Knowledge of dbt and/or Dataform, Terraform, Git, and CI/CD processes is desirable
  • Knowledge of Data Lake, Data Warehouse, and/or Lakehouse architectures
  • Knowledge of Hadoop and/or Kafka
  • Knowledge of relational and NoSQL databases
  • Knowledge of Machine Learning and/or Vertex AI
  • Knowledge of data governance and quality

Benefits

  • No specific benefits are listed; a Stefanini benefits section is present without further details

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