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Master Snowflake & dbt — Modern Analytics Engineering
Master the modern data stack with Snowflake & dbt — Snowflake architecture, Time Travel, SnowPark, dbt Core, dbt Cloud, data modeling, testing and CI/CD pipelines. Taught by Trainer Venu.
No prior experience needed
7-day money-back guarantee
Placement support included
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₹18,000
₹28,000
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0% EMI available · ₹2,500/month onwards
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Trainer Venu's team will call you within 2 hours.
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🎥 Live Online + Recorded Sessions
❄️ Real Snowflake Account Labs
📂 4 End-to-End Projects
📜 Certificate of Completion
🤝 Placement Support
♾️ Lifetime Recording Access
✅ Free Demo Before Enroll
Who Is This For
Is This Course Right For You?
❄️
Data Engineers
Build robust data pipelines loading into Snowflake with dbt transformations.
📊
Analytics Engineers
Master the analytics engineering discipline with dbt + Snowflake best practices.
🗄️
SQL / ETL Developers
Modernize from legacy ETL to dbt-driven transformation workflows.
☁️
Cloud Data Engineers
Add Snowflake and dbt to your AWS/Azure/GCP data engineering skill set.
🎓
Freshers
The Snowflake+dbt combo is one of the most in-demand modern data stack skills.
🏢
Data Architects
Design cost-efficient Snowflake architectures for enterprise analytics.
Tools Covered
❄️ Snowflake
🛠️ dbt Core
☁️ dbt Cloud
🔄 Airflow + dbt
📊 Cosmos
🔷 SnowPark
🔌 Snowpipe
🗄️ S3 / ADLS / GCS
🔍 Snowflake Marketplace
📋 Data Catalog
🧪 dbt Tests
🔀 CI/CD GitHub Actions
📈 Looker / Metabase
🤖 Cortex AI (Snowflake)
Course Curriculum
8 Modules — Key Concepts
Here are the core topics you'll master. Each module includes hands-on labs with real Snowflake + dbt access.
Module 01
Snowflake Architecture
- Virtual Warehouses — compute clusters on demand
- Database, Schema, Table hierarchy
- Micro-partitioning and automatic clustering
- Time Travel — query historical data snapshots
- Zero-copy cloning for dev/test environments
Module 02
Snowflake Data Loading
- COPY INTO — bulk loading from S3/ADLS/GCS
- Snowpipe — continuous auto-ingest from cloud storage
- Streams — CDC change tracking on tables
- Tasks — scheduled SQL execution
- Dynamic Tables — auto-updating materialized views
Module 03
dbt Core — SQL Transformations
- dbt models — SELECT statements as transformation units
- dbt materializations — table, view, incremental, ephemeral
- dbt Ref and Source functions
- dbt tests — generic and singular tests
- dbt docs — auto-generated data documentation
Module 04
dbt Advanced Patterns
- Incremental models — append, merge, delete+insert
- Snapshots — SCD Type 2 with dbt
- dbt Macros — Jinja templating for reusable SQL
- dbt Packages — dbt_utils, audit_helper, codegen
- dbt Seeds — load CSV data to warehouse
Module 05
SnowPark & Cortex AI
- SnowPark — Python DataFrames on Snowflake
- SnowPark ML — train ML models in Snowflake
- Cortex AI — LLM functions in SQL (COMPLETE, CLASSIFY)
- Snowflake Notebooks — interactive Python on Snowflake
- UDFs and Stored Procedures in Python/Java
Module 06
dbt Cloud & CI/CD
- dbt Cloud — managed dbt with IDE and scheduler
- dbt Cloud jobs — scheduled runs with alerts
- GitHub integration — PR checks with dbt CI
- dbt Semantic Layer — metrics definitions
- DataOps — version control, staging, production environments
M01
Snowflake Architecture & Setup
⏱️ 5 Hours● Beginner
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Snowflake Architecture — Cloud Services, Query Processing, Storage
Virtual Warehouses — XS to 6XL, auto-suspend/resume
Databases, schemas, tables — organization
Snowflake editions — Standard, Enterprise, Business Critical
Multi-cluster warehouses — concurrency scaling
Resource Monitors — credit usage alerts
Snowflake web UI and SnowSQL CLI
INFORMATION_SCHEMA and ACCOUNT_USAGE views
🔬 Snowflake Account Setup📝 Quiz: Architecture
M02
Snowflake Data Loading & Ingestion
⏱️ 6 Hours● Intermediate
▾
COPY INTO — load from S3, ADLS, GCS
Internal stages — named, table, user stages
External stages — S3/ADLS/GCS integration
File formats — CSV, JSON, Parquet, ORC, Avro
Snowpipe — serverless auto-ingest
Streams — append, insert, update change tracking
Tasks — serverless scheduled SQL execution
Dynamic Tables — auto-updating data pipelines
🔬 S3→Snowflake Pipeline🔬 Snowpipe Continuous Ingest
M03
Snowflake Advanced Features
⏱️ 6 Hours● Intermediate
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Time Travel — AT and BEFORE queries
Zero-copy cloning — databases, schemas, tables
Data Sharing — share data across accounts
Snowflake Marketplace — subscribe to data sets
Fail-Safe — 7-day disaster recovery
Search Optimization — point lookup acceleration
Column-level security — Dynamic Data Masking
Row-level security — Row Access Policies
🔬 Time Travel & Cloning Lab📝 Quiz: Advanced Features
M04
dbt Core — SQL Transformation Layer
⏱️ 8 Hours● Intermediate
▾
dbt project structure — models, seeds, tests, macros
dbt models — SELECT statements as transformation
dbt materializations — table, view, incremental, ephemeral
dbt Ref and Source functions for lineage
Generic tests — not_null, unique, accepted_values, relationships
Singular tests — custom SQL assertions
dbt docs — generate and serve documentation
dbt run, test, docs, seed, snapshot CLI commands
🔬 First dbt Project🔬 Incremental Models Lab🏗️ Project: dbt Data Mart
M05
dbt Advanced Patterns
⏱️ 6 Hours● Advanced
▾
Incremental strategies — append, merge, delete+insert, microbatch
Snapshots — SCD Type 2 with dbt
Jinja & Macros — reusable SQL templates
dbt Packages — dbt_utils, audit_helper, codegen, great_expectations
dbt Seeds — CSV to warehouse
dbt Exposures — document dashboards and reports
Hooks — pre/post model hooks for grants
dbt Variables and environment-specific configs
📝 Quiz: dbt Advanced
M06
SnowPark, Cortex AI & Python UDFs
⏱️ 6 Hours● Advanced
▾
SnowPark Python — DataFrames on Snowflake compute
SnowPark ML — train scikit-learn models on Snowflake
Cortex AI — COMPLETE, CLASSIFY, EXTRACT_ANSWER in SQL
Snowflake Notebooks — Python + SQL mixed workloads
Python UDFs — scalar and table functions
Java UDFs and Stored Procedures
Snowflake Scripting — procedural SQL
Vectorized Python UDFs for batch processing
🔬 SnowPark Python Lab🏗️ Project: Cortex AI Analytics
M07
dbt Cloud, CI/CD & DataOps
⏱️ 7 Hours● Advanced
▾
dbt Cloud — managed dbt IDE and scheduler
dbt Cloud environments — development, staging, production
dbt Cloud Jobs — scheduled and API-triggered runs
GitHub integration — PR-triggered CI checks
dbt Semantic Layer — centralized metric definitions
dbt Explorer — data lineage in dbt Cloud
Slim CI — only run changed models
DataOps practices — version control, testing, documentation
🔬 dbt Cloud CI/CD Setup🏗️ Project: Full Modern Data Stack
M08
End-to-End Projects & Career Prep
⏱️ 6 Hours● Advanced
▾
Project 1 — Batch: S3 → Snowflake → dbt → Looker dashboard
Project 2 — Streaming: Snowpipe + Streams + Tasks auto-pipeline
Project 3 — Analytics Engineering: Full dbt data mart with docs
Project 4 — Modern Stack: Airflow + Snowflake + dbt + Cortex AI
Snowflake SnowPro Core certification prep
dbt Fundamentals certification guide
Resume & LinkedIn for analytics engineering roles
🏗️ 4 Real Projects📝 Certification Prep
Career Outcomes
Snowflake + dbt Professionals Earn Top Salaries
Analytics engineers with Snowflake + dbt expertise are in very high demand. This modern data stack combination is the standard at top companies globally.
Entry Level
₹10–18 LPA
0–2 Years
Mid Level
₹18–32 LPA
2–5 Years
Senior Level
₹32–60+ LPA
5+ Years
Student Success Stories
1200+ Professionals Placed at Top Companies
★★★★★
"The dbt incremental models and SnowPark modules were outstanding. Trainer Venu covered topics I've not seen in any YouTube course. Got placed at Deloitte!"
KS
Kavya Sharma
SQL Dev → Analytics Engineer
✅ Deloitte · ₹22 LPA
★★★★★
"dbt Cloud CI/CD and the modern data stack project were exactly what the industry wants. Landed a great role at a fintech startup after this training!"
TR
Tarun Reddy
Data Analyst → Data Engineer
✅ Fintech · ₹26 LPA
★★★★★
"Time Travel, Zero-copy cloning and Dynamic Tables modules were very practical. The Snowpipe lab on real accounts was excellent!"
LD
Lakshmi Devi
ETL Dev → Data Engineer
✅ Infosys · ₹16 LPA
FAQs
Frequently Asked Questions
Do I get access to a real Snowflake account? ▾
Yes! Snowflake offers a 30-day free trial with $400 credits. All labs use real Snowflake accounts. We guide you through setup in the first session.
What is dbt and why is it important? ▾
dbt (data build tool) is the standard SQL transformation tool used by analytics engineers at top companies. It adds version control, testing, docs and CI/CD to SQL — making data transformations production-grade.
Does this course cover Snowflake certification? ▾
Yes — Module 8 includes prep for the SnowPro Core certification (COF-C02) and the dbt Fundamentals certification.
Is Airflow + dbt + Snowflake covered together? ▾
Yes — we cover the full modern data stack: Airflow orchestrates dbt runs against Snowflake. Module 8 has a complete end-to-end project combining all three.
What salary can I expect after this course? ▾
Entry level: ₹10–18 LPA. Analytics engineers with dbt + Snowflake expertise at mid-level earn ₹18–32 LPA. Senior roles pay ₹32–60+ LPA.