GCP Data Engineer
Required skills
Experience in Data Engineering, including significant experience on GCP. Strong skills in SQL and data-oriented programming. Mastery of at least several GCP data-oriented services (BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage...). Experience with PySpark or Spark for data processing. Knowledge of Data Lake and Data Warehouse architectures on GCP. Sensitivity to security, governance, and cost optimization. Ability to work in a team and communicate with technical and business profiles.
Technologies
BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, Composer, Looker, PySpark, Spark, Cloud Composer (Airflow), IAM, Data Catalog, DLP, SQL, Python, Azure Data Factory, Power BI, Tableau, .Net, Java, Node.js, AWS, Azure, GCP.
Responsibilities
Design, develop, and maintain data pipelines on GCP. Integrate and transform data from various sources (SQL/NoSQL databases, APIs, ERP, CRM, flat files...). Use GCP services such as BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, Composer, or Looker. Develop distributed and optimized processing with PySpark or Spark on Dataproc. Orchestrate and automate workflows with Cloud Composer (Airflow) or equivalents. Implement data quality, consistency, and security controls (IAM, Data Catalog, DLP...). Optimize processing performance and master infrastructure costs. Document data flows and ensure their traceability. Collaborate with Data and IT teams to provide ready-to-use datasets. Participate in technological monitoring on GCP and cloud data solutions.
Seniority
Not specified.
Domain
Data Intelligence, Cloud Native Development, Serverless Architecture.
