Master GCP Data Engineering — BigQuery, Dataflow, Dataproc & Pub/Sub

Master Google Cloud Data Engineering — BigQuery for analytics, Dataflow for ETL, Dataproc for Spark, and Cloud Composer for orchestration — all with Trainer Venu. Includes GCP Professional Data Engineer exam prep.

⏱️ 60 Hours

📦 9 Modules

🔬 18+ Labs

🗂️ 4 Projects

📜 PDE Cert Prep

No prior experience needed

7-day money-back guarantee

Placement support included

Is This Course Right For You?

🌐

Cloud Engineers

Build production GCP data pipelines using BigQuery, Dataflow and Dataproc.

📊

BigQuery Analysts

Move from SQL analysis to building full data engineering pipelines on GCP.

⚡

PySpark Developers

Run Spark workloads on Dataproc with BigQuery as the data warehouse.

🎓

Freshers

Target GCP data engineering roles at Google, Wipro, TCS with great salaries.

🔄

Airflow Engineers

Add Cloud Composer (managed Airflow) expertise to your skill set.

🏢

Data Architects

Design enterprise analytics platforms on Google Cloud.

Tools Covered

📊 BigQuery

🌊 Dataflow (Apache Beam)

⚡ Dataproc (Spark)

📨 Cloud Pub/Sub

🔄 Cloud Composer

🗄️ Cloud Storage (GCS)

🔍 Looker Studio

🧊 BigLake

📋 Data Catalog

🔐 IAM & VPC

🔥 Databricks on GCP

🐍 PySpark / Apache Beam

📜 GCP PDE Cert

Course Curriculum

9 Modules — Key Concepts

Here are the core topics you'll master. Each module includes hands-on labs with real GCP Data Engineering access.

Module 01

BigQuery — Cloud Data Warehouse

BigQuery architecture — slots, reservations, datasets
Partitioned and clustered tables for cost optimization
BigQuery ML — train ML models with SQL
BigQuery Omni — query S3/Azure data
Authorized Views and row-level security

Module 02

Dataflow — Serverless ETL

Apache Beam programming model — PCollections, PTransforms
Batch and streaming Dataflow pipelines
Dataflow Flex Templates — reusable pipelines
Dataflow → BigQuery — streaming inserts
Auto-scaling and windowing strategies

Module 03

Dataproc — Managed Spark

Dataproc cluster setup — master, worker nodes
PySpark jobs on Dataproc
Dataproc Serverless — no cluster management
Dataproc Metastore — Hive-compatible catalog
BigQuery connector for Dataproc

Module 04

Cloud Pub/Sub & Streaming

Pub/Sub topics, subscriptions, push vs pull
Pub/Sub to Dataflow streaming pipelines
Pub/Sub → BigQuery direct subscription
Dead-letter topics and retry policies
Eventarc — event-driven pipelines

Module 05

Cloud Composer — Orchestration

Cloud Composer = managed Apache Airflow on GCP
DAG deployment to Cloud Composer
GCP operators — BigQuery, GCS, Dataflow, Dataproc
Composer environments — Small, Medium, Large
Monitoring with Cloud Monitoring

Module 06

Data Catalog & Governance

Data Catalog — search, tag, lineage
BigLake — unified access control
Column-level security in BigQuery
VPC Service Controls — data perimeter
Dataplex — data mesh on GCP

M01

GCP Fundamentals for Data Engineers

⏱️ 4 Hours● Beginner

▾

GCP Console, projects, billing accounts

IAM — service accounts, roles, custom roles

Cloud Storage (GCS) — buckets, lifecycle, ACLs

VPC and private connectivity for data services

Cloud SDK — gcloud, gsutil, bq CLI

Cloud Monitoring and Logging basics

🔬 GCP Environment Setup📝 Quiz: GCP Fundamentals

M02

BigQuery — Enterprise Data Warehouse

⏱️ 10 Hours● Intermediate

▾

BigQuery architecture — serverless, columnar storage

Datasets, tables, views — organization

Partitioned tables — date, range, ingestion-time

Clustered tables — multi-column clustering

BigQuery DML — INSERT, UPDATE, DELETE, MERGE

BigQuery Scripting — variables, loops, procedures

BigQuery ML — train models with SQL

BigQuery Omni — cross-cloud queries

Authorization — row-level, column-level security

Cost optimization — partitioning, clustering, reservations

🔬 BigQuery Data Warehouse Build🔬 BigQuery ML Lab🏗️ Project: BigQuery Analytics Platform

M03

Google Cloud Storage & Data Lake

⏱️ 4 Hours● Beginner

▾

GCS storage classes — Standard, Nearline, Coldline

Object lifecycle management and versioning

Signed URLs and IAM access control

GCS as data lake — Parquet, ORC, Avro, Delta

Gsutil parallel uploads and transfers

GCS notifications — Pub/Sub and Cloud Functions

🔬 GCS Data Lake Setup

M04

Cloud Dataflow — Apache Beam ETL

⏱️ 9 Hours● Advanced

▾

Apache Beam fundamentals — PCollections, transforms

ParDo, GroupByKey, CoGroupByKey, Combine

Batch Dataflow pipelines — GCS→BigQuery

Streaming Dataflow — Pub/Sub→BigQuery

Windowing — Fixed, Sliding, Session windows

Watermarks and late data handling

Dataflow Flex Templates — containerized pipelines

Dataflow Shuffle — Batch Pipeline optimization

🔬 Batch Pipeline: GCS→BigQuery🔬 Streaming: Pub/Sub→Dataflow→BQ🏗️ Project: Real-time Dataflow Pipeline

M05

Cloud Dataproc — PySpark on GCP

⏱️ 8 Hours● Intermediate

▾

Dataproc cluster — master, worker, preemptible nodes

Submit PySpark, Hive, SparkSQL jobs

Dataproc Serverless — no cluster management

Dataproc Metastore — fully managed Hive Metastore

BigQuery connector — Spark→BigQuery reads/writes

Cloud Storage connector — HDFS replacement

Initialization actions — custom packages

Autoscaling policies for cost optimization

🔬 PySpark on Dataproc Lab🏗️ Project: Dataproc + BigQuery Pipeline

M06

Cloud Pub/Sub & Event-Driven Pipelines

⏱️ 6 Hours● Advanced

▾

Pub/Sub architecture — topics, subscriptions

Push vs Pull subscriptions

Pub/Sub ordering keys and message deduplication

Dead-letter topics — error handling

Pub/Sub → BigQuery direct subscription

Eventarc — trigger Cloud Functions/Run from events

Real-time CDC: Pub/Sub → Dataflow → BigQuery

🔬 Pub/Sub Streaming Pipeline

M07

Cloud Composer — Orchestration

⏱️ 5 Hours● Intermediate

▾

Cloud Composer = managed Airflow on GCP

Composer 2 — auto-scaling, workload identity

DAG deployment — GCS-backed storage

GCP operators — BigQueryOperator, GCSToGCSOperator, DataflowOperator, DataprocOperator

XComs, Variables, Connections on Composer

Monitoring with Cloud Monitoring and Alerting

🔬 Cloud Composer DAG Lab

M08

Data Catalog, Dataplex & Governance

⏱️ 5 Hours● Advanced

▾

Data Catalog — tagging, search, policy tags

BigLake — unified storage access control

Dataplex — data mesh zones and lakes

Column masking and row-level access

VPC Service Controls — perimeter security

Audit logging for compliance

Data lineage with Dataplex

📝 Quiz: Data Governance & Security

M09

Projects & GCP Professional Data Engineer Prep

⏱️ 9 Hours● Advanced

▾

Project 1 — Batch ETL: GCS → Dataflow → BigQuery → Looker

Project 2 — Streaming: IoT Pub/Sub → Dataflow → BigQuery

Project 3 — Big Data: Dataproc PySpark + BigQuery

Project 4 — Full Platform: Composer + Dataflow + BigQuery + Dataplex

GCP Professional Data Engineer exam prep

100+ practice questions with explanations

Resume and LinkedIn optimization for GCP roles

🏗️ 4 Real GCP Projects📝 PDE Mock Tests

Master GCP Data Engineering — BigQuery, Dataflow, Dataproc & Pub/Sub

✅ Demo Booked!

Is This Course Right For You?

9 Modules — Key Concepts

GCP Data Engineering Professionals Earn Top Salaries

1200+ Professionals Placed at Top Companies

Frequently Asked Questions

Start Your Journey Today