Teach me ETL pipelines on GCP | Data Engineering

@bizmanas

Hello, Your project about mastering end-to-end ETL pipelines on Google Cloud in a one-week bootcamp immediately caught my attention. From your description, you want a fully hands-on learning experience where we build, deploy, monitor, and troubleshoot real GCP pipelines using tools like Dataflow, Pub/Sub, BigQuery, Composer, and Looker until you can run them independently. I’m a data engineering and cloud architect with 18+ years of experience, working extensively with Google Cloud, Azure, and large-scale data platforms. I maintain a 4.9 client rating and strong repeat client relationships because I focus on practical learning and real production patterns rather than just theory. My expertise includes ETL pipelines, BigQuery architecture, Dataflow streaming pipelines, Terraform-based infrastructure, and orchestration with Airflow/Cloud Composer. Here’s how I would structure the week to maximize hands-on learning: • Day 1 – GCP Data Engineering Foundations Set up environment, IAM, Terraform basics, and ingestion patterns using Pub/Sub + Cloud Storage. • Day 2 – Streaming & Batch Pipelines Build ETL pipelines using Dataflow (Apache Beam) for both streaming and batch processing. • Day 3 – Storage Architecture Load transformed data into BigQuery, Bigtable, and Cloud SQL, and discuss when to use each. • Day 4 – Data Transformation & Orchestration Build workflows using Cloud Composer (Airflow), integrate Cloud Functions and Scheduler. will share full course content

@emanuelgm777

GCP ETL Fast-Track: Production-Ready Pipelines in 3 Days ​Deploying Terraform IaC, Dataflow (Apache Beam), and Pub/Sub event-driven architectures. I offer an intensive 3-day technical sprint: from Cloud Composer orchestration to BigQuery optimization. ​Timeline: 3 Days (Full-time). Stack: GCP, Python, SQL, Terraform.

@akshithach9

Hello, I’m excited to help you master end-to-end ETL pipelines on GCP in a focused, hands-on week. With 2+ years of experience as a GCP Data Engineer, I’ve built and managed scalable pipelines using GCS, BigQuery, and Cloud Composer (Airflow), including real-world data migration (Teradata → BigQuery) and production-grade ingestion and transformation workflows. My approach matches your requirement: live sessions where I demonstrate, then guide you as you implement the same steps. We will focus on practical execution—Dataflow, Pub/Sub, GCS for ingestion; transformations using Dataflow/Dataproc; storage across BigQuery and other services; and orchestration via Cloud Composer, Scheduler, and Functions. I’ll also cover monitoring, debugging, logging, and basic Terraform/gcloud usage for real-world readiness. In 7 days (3–4 hrs/day), we’ll build a complete pipeline—from ingesting a public dataset to transforming, storing in multiple targets, and visualizing via Looker Studio—fully orchestrated and reusable. You’ll receive recorded sessions, step-by-step labs, scripts, and a final project you can run independently, plus a post-bootcamp practice plan. I focus on making you confident enough to build and troubleshoot pipelines on your own. Looking forward to working with you! Best regards, Akshitha