🔷 Premium Certification Track

GCP Data Engineer Training in Hyderabad

Master Google Cloud's data engineering tools — BigQuery, Dataflow, Pub/Sub, Dataproc. Build real data pipelines on GCP and prepare for the Professional Data Engineer certification from Ameerpet.

📋 Course Quick Facts

3.5 Months Duration
Online + Offline Mode
6+ Real Projects
6–24 LPA Salary

✅ Free demo · No commitment · Reply in 15 mins

🏆 8+ Years Trainer Experience
📁 6+ Real GCP Pipeline Projects
🎓 GCP Data Engineer Certified
💼 100% Placement Support
💰 Salary: 6–24 LPA
Why GCP for Data Engineering

BigQuery is Changing How Companies Do Analytics

If you've worked with data in any capacity, you'll understand what BigQuery feels like the moment you run your first petabyte-scale query and get results in seconds — at a fraction of the cost of running your own infrastructure. That's not marketing; that's why Hyderabad's fastest-growing product companies are all moving their analytics to GCP.

This course takes you through the complete GCP data engineering stack. You'll design batch pipelines with Dataflow and Apache Beam, handle real-time event streaming with Pub/Sub, run distributed Spark jobs on Dataproc, and orchestrate everything with Cloud Composer (managed Airflow).

By the time you finish, you'll have 6+ production-grade pipeline projects in your portfolio and be fully prepared for the GCP Professional Data Engineer exam — one of the most respected cloud certifications in the industry.

🎯 Who Should Join This Course?

  • Freshers with Python / SQL wanting data engineering careers
  • AWS data engineers adding GCP to their multi-cloud profile
  • ETL developers moving to cloud-native data pipelines
  • BI analysts wanting to build backend data pipelines
  • Anyone targeting GCP Professional Data Engineer exam
  • Data analysts at companies migrating to BigQuery

📌 Prerequisites

Basic Python and SQL knowledge is helpful. Module 1 covers Python + SQL fundamentals, so non-technical backgrounds are welcome. No prior GCP experience needed.

Full Curriculum

What You Will Learn

8 modules — Python/SQL foundation to production-grade GCP data pipelines and Professional Data Engineer exam prep.

1

Python, SQL & GCP Fundamentals

  • Python for data engineering — Pandas, file handling, APIs
  • Advanced SQL — window functions, CTEs, optimisation
  • GCP Console, Cloud Shell, gcloud CLI basics
  • IAM for data engineers — service accounts, roles
  • GCP storage hierarchy — projects, buckets, datasets
2

BigQuery — Google's Serverless Data Warehouse

  • BigQuery architecture — slots, reservations, storage
  • Partitioned and clustered tables for performance and cost
  • BigQuery ML — training models with SQL
  • BigQuery Omni — querying AWS S3 and Azure Blob from BigQuery
  • Data Studio / Looker integration for visualisation
3

Cloud Storage & Data Lake on GCP

  • Cloud Storage — bucket types, lifecycle management, versioning
  • Data Lake design on GCS — bronze, silver, gold zones
  • Cloud Storage to BigQuery — external tables and direct load
  • Data Transfer Service for bulk migrations to GCP
4

Apache Beam & Dataflow — Unified Batch/Stream

  • Apache Beam programming model — PCollections, transforms
  • Dataflow — managed Beam runner on GCP
  • Windowing strategies — fixed, sliding, session windows
  • Dataflow Flex Templates for portable pipelines
  • Dataflow monitoring, profiling, and cost control
5

Pub/Sub — Real-Time Messaging

  • Pub/Sub topics, subscriptions, and message delivery
  • Push vs pull subscriptions — use cases and trade-offs
  • Pub/Sub to BigQuery — real-time ingestion pipeline
  • Pub/Sub to Dataflow — streaming ETL patterns
  • Ordering, deduplication, and dead-letter topics
6

Dataproc — Managed Spark & Hadoop

  • Dataproc cluster creation — single node, standard, HA
  • Apache Spark on Dataproc — PySpark jobs, structured streaming
  • Apache Hive and Pig on Dataproc
  • Dataproc Serverless Spark — auto-scaling without cluster management
  • Connecting Dataproc to BigQuery and Cloud Storage
7

Cloud Composer — Managed Apache Airflow

  • Cloud Composer environment setup and architecture
  • DAG design — tasks, dependencies, sensors, operators
  • GCP operators — BigQueryOperator, DataflowOperator, DataprocOperator
  • Dynamic DAGs for parameterised pipelines
  • Monitoring and alerting for Composer DAGs
8

Data Quality, Governance & Security

  • Dataplex — data mesh and data quality on GCP
  • Data Catalog — metadata management and discovery
  • Column-level and row-level security in BigQuery
  • VPC Service Controls for data perimeter
  • Cloud DLP for PII detection and de-identification
📄 Download Full Syllabus PDF
GCP Data Stack

Tools & GCP Services You'll Master

Analytics & Warehousing

BigQuery BigQuery ML Looker Data Studio Looker Studio

Storage & Data Lake

Cloud Storage Cloud Bigtable Cloud Spanner Firestore Data Catalog

Streaming & Messaging

Pub/Sub Dataflow Apache Beam Datastream Change Data Capture

Batch & Big Data

Dataproc Apache Spark Apache Hive PySpark Dataproc Serverless

Orchestration & Governance

Cloud Composer Apache Airflow Dataplex Cloud DLP Data Lineage

Security & Developer Tools

IAM VPC Service Controls Cloud DLP gcloud CLI Terraform
Hands-On Projects

6+ Real GCP Data Pipeline Projects

📦

BigQuery Data Warehouse

Design a star-schema data warehouse in BigQuery for e-commerce analytics. Load 50M+ rows from Cloud Storage, create partitioned tables, build Looker Studio dashboard.

Real-Time Event Pipeline

Pub/Sub → Dataflow → BigQuery real-time pipeline processing clickstream data. Handle late arrivals with watermarks, build live monitoring dashboard.

🔄

Batch ETL with Dataflow + Apache Beam

Build a reusable Dataflow pipeline with Apache Beam that reads from GCS, applies complex transformations, and writes to both BigQuery and Cloud Spanner.

🌊

Spark Pipeline on Dataproc

Process 10GB+ of raw log data using PySpark on Dataproc Serverless. Sessionise user journeys, aggregate metrics, and write results to BigQuery partitioned tables.

🔁

Orchestrated Data Platform

Build a Cloud Composer (Airflow) orchestrated data platform — daily Dataproc jobs, BigQuery transforms, data quality checks, and alerting on failures.

🛡️

Secure Data Lake with Dataplex

Design a governed data lake with Dataplex — zone management, metadata tagging, data quality rules, column-level security in BigQuery, and audit logging.

Career Outlook

GCP Data Engineer Salaries in Hyderabad — 2026

ExperienceRoleHyderabad Salary
Fresher (0–1 yr)Junior Data Engineer, BigQuery Analyst₹6–9 LPA
1–3 YearsGCP Data Engineer, Cloud Data Engineer₹9–16 LPA
3–5 YearsSenior Data Engineer, Data Architect₹15–22 LPA
5+ YearsData Engineering Lead, Principal Engineer₹22–35 LPA

Build Your GCP Data Engineering Career in Hyderabad

BigQuery skills are rare in Hyderabad — and that means premium salaries for the people who have them. Join us and be one of them.

📍 Ameerpet, Hyderabad · Online Available Across India

FAQ

Frequently Asked Questions

GCP Data Engineer training covers building scalable real-time and batch data pipelines on Google Cloud Platform using BigQuery, Dataflow, Pub/Sub, Dataproc, and Apache Beam. Our Hyderabad training at Ameerpet is 100% hands-on with 6+ real data pipeline projects on actual GCP accounts.

Basic Python and SQL knowledge is helpful. We cover Python and SQL fundamentals in Module 1. Students from non-technical backgrounds in Ameerpet and across Hyderabad have successfully completed this course after the foundation module.

BigQuery is Google Cloud's serverless, petabyte-scale data warehouse. It is the most powerful tool for analytics and BI on GCP. Companies in Hi-Tec City, Gachibowli, and Madhapur increasingly use BigQuery for their data needs, making BigQuery skills highly valuable in Hyderabad's job market.

We primarily prepare you for the Google Cloud Professional Data Engineer certification — one of the highest-value GCP certs. We also cover the Associate Cloud Engineer as a foundation. Exam prep includes practice tests, study materials, and exam strategies specific to Hyderabad's hiring patterns.

Yes! We have live online batches for students from Ameerpet, Hi-Tec City, Gachibowli, and all parts of Hyderabad. Same trainer, same 6+ data pipeline projects on real GCP accounts, same placement support. Online students from Ameerpet have got placed in top Hyderabad companies.

After GCP Data Engineer training you can work as: GCP Data Engineer, BigQuery Specialist, Cloud Data Analyst, Data Pipeline Developer, Data Platform Engineer. Companies in Hi-Tec City, Gachibowli, Madhapur, and Ameerpet are hiring with salaries from ₹7–24 LPA.

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