.**RH**:Raul García**Position**:GCP Data Engineer**Location**:Aguascalientes, Mexico**Industry - Sector**:MALS**What you'll do?**- Build, maintain, and optimize end-to-end ETL pipelines using Google Cloud Dataflow, Apache Beam, Cloud Composer, and Cloud Functions.- Automate data ingestion, transformation, and integration processes from multiple sources (structured and unstructured data) into cloud-based data platforms.- Design and implement scalable cloud-based data architectures using services like Google BigQuery, Google Cloud Storage (GCS), Cloud Pub/Sub, and Cloud Dataproc.- Architect data solutions that are reliable, performant, and cost-effective for large-scale data processing and storage needs.- Build and manage data lakes using Google Cloud Storage and ensure data is properly ingested, stored, and processed in an organized and secure manner.- Implement Google BigQuery data warehouses, optimize data models for performance, and ensure they are scalable to handle large datasets.- Leverage Google Cloud Dataflow or Apache Beam to transform data into formats suitable for reporting and machine learning models.- Integrate diverse data sources such as relational databases, NoSQL databases, APIs, and flat files into the data pipeline architecture.- Automate the deployment of data pipelines, processes, and infrastructure using Google Cloud Deployment Manager, Terraform, or Cloud Composer.- Design and manage CI/CD pipelines for efficient deployment of data engineering solutions.- Implement best practices for data governance, ensuring data privacy and compliance with security standards (e.G., encryption, data masking, and access control).- Manage permissions and security with Google IAM, and ensure that sensitive data is securely handled and stored.- Continuously monitor the performance of data pipelines and storage solutions, identifying opportunities for optimization and cost reduction.- Troubleshoot and resolve data integration and pipeline issues to ensure smooth and efficient data processing.- Collaborate with cross-functional teams (data scientists, analysts, business stakeholders) to understand data requirements and deliver high-quality data solutions.- Provide support for data-related questions, troubleshooting, and assist with data visualization and reporting tasks.- Document data engineering processes, including pipeline architectures, configurations, and best practices.- Prepare and deliver regular updates on data engineering projects and their progress.**What you'll bring**:- Expertise in Google Cloud BigQuery, Google Cloud Storage (GCS), Cloud Dataflow, Cloud Pub/Sub, Google Cloud Dataproc, Cloud Composer, Cloud Functions, and Cloud Bigtable.- Experience in building ETL pipelines using Cloud Dataflow, Apache Beam, Google Cloud- Ability to integrate structured and unstructured data sources into cloud-based systems