BUILD SKILLS COMPANIES PAY FOR
Become a GCP Data Engineer
Work on Real-Time Data Pipelines
Learn BigQuery, Dataflow, Pub/Sub, and Cloud Composer through practical, industry-grade projects, live mentor guidance, and interview-focused training—no prior cloud experience required. Gain hands-on experience building batch and real-time data pipelines, designing high-performance data warehouses, and orchestrating workflows using production-ready GCP architectures.
You’ll work on real enterprise use cases, apply cost optimization, security, and monitoring best practices, and gain the confidence to design, explain, and defend data architectures in real interviews—skills actively used by top technology companies.
⭐ Trusted by 3,000+ Learner
100% Success Rate
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100% Success Rate
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Ideal For
Fresher
Professional Upskillers
Working Professionals
Cloud Engineering Experts
Cloud Engineers
Analytical Professionals
Analysts
Career Changers
Career Switchers
Why Choose LevelUp for GCP Data Engineering?
Enterprise GCP Data Engineering Projects
Build complete batch and real-time data platforms using GCS, Dataflow, BigQuery, Pub/Sub, and Airflow, following real enterprise architectures.
BigQuery Data Warehousing & Query..
Design high-performance data warehouses using advanced SQL, partitioning, clustering, slot management, and cost-efficient query patterns.
Apache Beam Pipelines on Dataflow
Develop scalable batch and streaming pipelines with windowing, triggers, error handling, autoscaling, and production deployment patterns.
Event-Driven Streaming with Pub/S..
Implement real-time event ingestion using topics, subscriptions, ordering, dead-letter queues, and secure messaging architectures.
Cloud Composer
(Airflow) orchestration
Orchestrate complex data workflows across GCS, Dataflow, BigQuery, Spark, and Pub/Sub with monitoring, retries, and SLAs.
DataOps, CI/CD & Observability on GCP
Automate pipeline deployments and manage logging, monitoring, alerts, and SLA-based reliability for data platforms.
Enterprise Project Reviews & Architecture Mentorship
Receive industry-style reviews focused on architecture design, performance tuning, security, cost optimization, and best practices.
What You Will Learn
GCS (Google Cloud Storage)
BigQuery (Partitioning...
Dataflow (Batch + Streaming)
Dataproc (Spark/Hadoop)
Vertex AI Basics (Optional)
Cloud Composer (Airflow)
Pub/Sub
Messaging
IAM & Cloud Security
Cost
Optimization
End-to-End GCP Pipelines
Our Curriculum
Concepts
- What is Data Engineering (vs Data Science & Analytics)
- Batch vs Streaming processing
- Modern data architectures (OLTP vs OLAP)
- Intro to Big Data & distributed computing
- Why Spark & PySpark matter
GCP Basics
- GCP global infrastructure (regions, zones)
- Resource hierarchy (Org → Folder → Project)
- IAM & service accounts (intro)
Hands-on
- GCP account & project setup
- Cloud Shell & gcloud CLI
- Basic Python refresh (for PySpark readiness)
Concepts
- Object storage & data lakes
- File formats (CSV, JSON, Parquet, Avro)
- Partitioning strategies for big data
- Cost & lifecycle management
Hands-on
- Create GCS buckets
- Upload structured & semi-structured data
- Organize raw / curated / processed zones
- Cost & lifecycle management
➡️ Sets up data for PySpark & Databricks
Concepts
- Spark architecture (Driver, Executor)
- RDD vs DataFrame
- Lazy evaluation
- Transformations vs Actions
PySpark Hands-on
- Create Spark session
- Read data from GCS
- DataFrame operations
- Filtering, joins, aggregations
- Write Parquet output
Concepts
- Spark SQL
- Window functions
- UDFs
- Partitioning & bucketing
- Caching & persistence
- Shuffle optimization
Hands-on
- Build production-grade PySpark ETL
- Handle bad records
- Optimize slow Spark jobs
Concepts
- What is Databricks
- Lakehouse architecture
- Databricks vs Dataproc vs Dataflow
- Delta Lake (ACID, Time Travel, Schema Evolution)
Hands-on
- Databricks workspace & clusters
- PySpark notebooks
- Delta tables
- Incremental ETL using Delta Lake
Concepts
- Serverless data warehouse
- Storage vs compute
- Managed vs external tables
- Billing & pricing
Hands-on
- Load data from GCS / Databricks output
- Query datasets
- BigQuery UI & CLI
Concepts
- Window functions
- Nested & repeated fields
- Partitioning & clustering
- Cost-optimized query design
Hands-on
- Build analytics-ready tables
- Optimize expensive queries
Concepts
- When to use Spark vs Dataflow
- Apache Beam model
- Dataflow architecture
Hands-on
- Batch pipelines (GCS → BigQuery)
- Error handling & monitoring
Concepts
- Event-driven architecture
- Streaming guarantees
- Windowing & triggers
Hands-on
- Real-time ingestion pipeline
- Streaming ETL into BigQuery
Concepts
- Managed Spark & Hadoop
- Dataproc vs Databricks
- Cluster tuning & autoscaling
Hands-on
- Run PySpark jobs on Dataproc
- Compare performance with Databricks
- Cluster tuning & autoscaling
Concepts
- Workflow orchestration
- DAGs, operators, sensors
- Retry & failure handling
Hands-on
- Orchestrate PySpark, Databricks & Dataflow jobs
- Data security & IAM
- BigQuery ML
- Looker Studio
- DataOps & CI/CD
- Capstone: End-to-end PySpark + Databricks + GCP project
Level Up has helped build 5000+ Careers
What You Will Learn
BigQuery
GCS
Dataflow
Dataproc
Cloud Composer
Pub/Sub
Vertex AI (optional)
Cloud Build
Meet Our founder
Sateesh pabbathi
I’m Sateesh Pabbathi, Founder and CEO of LevelUp Cloud Trainings Pvt. Ltd., with 20+ years of hands-on experience in Cloud Computing, Data Engineering, and DevOps. I’ve delivered large-scale global projects across AWS, Azure, and GCP—not theory, not slides, but real production systems used by real companies. Today, I leverage that exact industry experience to help IT professionals transition into high-paying Data Engineering roles in just 90 days. Over the years, I’ve helped professionals break out of support, testing, and non-technical roles and move into core Data Engineering positions with strong career and salary growth through project-driven, interview-focused training. My approach emphasizes hands-on labs, real-world use cases, and resume-ready projects, while simplifying complex cloud and data concepts into practical, job-ready frameworks—all with a clear focus on measurable career outcomes, not just certifications.
Projects
GCS → Dataflow → BigQuery Analytics Pipeline
Real-time Pub/Sub
streaming
Spark ETL
on Dataproc
Data Warehouse
Design in BigQuery
Airflow-based
data orchestration
Real word project that will not just tech you tools, instead make you real industry ready professional.
Project Demo
Trainer Info
Instructor Name
Course taught by GCP Certified Data Engineers with real-world enterprise migration experience.
Expertise
- BigQuery & Data Analytics
- Dataflow & Streaming Pipelines
- Dataproc & Spark ETL
- Pub/Sub & Cloud Composer
- CI/CD & Cloud DevOps
Every concept is taught with real project context — exactly how it’s used in production systems.
Experience
8+ years in Cloud & Data Engineering
Worked With
oogle Cloud Partner Firms, MNCs, SaaS
Our 3-Step Approach to Get You Interview-Ready and Placed
🚀 Profile Building That Gets You HIRED
- Recruiter-approved, ATS-cracking resumes that actually get shortlisted
- LinkedIn profiles engineered to attract recruiters, not just look good
- Personal branding built across top hiring platforms used by real companies
- Profiles customized specifically for high-paying Data Engineering & Cloud roles
👉 Stop getting ignored. Start getting interview calls.
01
🤝 Referrals That Open Doors
- Direct referrals through our elite alumni & mentor network
- Access to hidden job openings that never reach job portals
- Personal referrals from instructors who actively recommend you
- Proven referral strategies that multiply interview chances
👉 Referrals beat applications. We make sure you get them.
02
🏢 Company Tie-Ups That Convert to Interviews
- 500+ active hiring partners across product, MNC, and startup ecosystems
- Hand-picked job opportunities matched to your skill readiness
- Real interview connections with top tech and product firms
- Continuous access to live openings, hiring drives, and fast-track interviews
👉 We don’t just train you. We connect you to companies that hire.
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Career Outcomes
Graduates typically move into roles such as
GCP Data Engineer
Cloud Data Engineer
Big Data Engineer
Analytics Engineer
Hiring companies: Product firms, MNCs, fintech, healthcare, SaaS companies
Student Success Stories
Ankit Sharma
The real-time projects and Databricks training helped me switch careers confidently.
Before
Manual QA Engineer
After
Manual QA Engineer
FinTech Startup
Priya Nair
Medallion architecture and streaming pipelines were exactly what interviewers asked.”
Before
Data
Analyst
After
Senior Azure Data Engineer
FinTech Startup
Rahul Mehta
LevelUp gave me real project experience even before my first job
Before
Manual QA Engineer
After
Manual QA Engineer
FinTech Startup
FAQ's
Course taught by Azure Data Engineering Architects with real project experience in enterprise-scale data pipelines.
Q1. Is GCP suitable for freshers?
Yes — very beginner friendly.
Q2. Will we learn BigQuery deeply?
Yes, with cost optimization & cluster tuning.
Q3. Are live labs included?
Yes — through OTT + Live projects.
Free Webinar & Demo Access
Register for Free Live Webinar
Get a sneak peek into the GCP Data Engineer Program, see real-time projects in action, and interact with our instructors.