We are looking for a Senior Data Engineer with solid experience in cloud data platforms, especially in the Google Cloud Platform (GCP) ecosystem. This professional will be responsible for designing, building, maintaining, and monitoring scalable and resilient data pipelines, ensuring high performance, governance, and reliability of information in analytical environments.

Key Technical Competencies

• Solid experience in cloud data engineering with a focus on Google Cloud Platform (GCP), using services such as BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, Cloud Functions, and Composer.
• Experience in developing and optimizing large-scale data ingestion, transformation, and processing pipelines.
• Experience with Databricks or Spark for distributed data processing.
• Implementation of observability in data pipelines, using monitoring, logging, metrics, and alerting tools to ensure data quality and reliability.
• Experience in creating reusable frameworks and templates for orchestration and standardization of data pipelines.
• CI/CD practices applied to data projects, including code versioning, deployment automation, and continuous integration.
• Application of data engineering best practices, such as data modeling, partitioning, governance, cataloging, and data security.
• Experience in architecture and performance optimization in Power BI, including data modeling, DAX, workspace governance, and best practices for corporate environments.
• Management of access, identity, and integration between environments (IAM, security policies, and data governance).

Desirable Differentiators

• Google Cloud (GCP) Certifications, such as Professional Data Engineer or Professional Cloud Architect.
• Experience with large data volumes (Big Data) and event-driven architectures.
• Knowledge of tools such as Apache Airflow / Cloud Composer, dbt, Spark, or other data orchestration and transformation solutions.
• Experience with modern data architectures (Data Lake, Lakehouse, Data Mesh).
• DevOps/DataOps mindset, with a focus on automation, quality, and pipeline reliability.