About Course
About Data Engineering with Snowflake Training
Gurugram's DLF Cyber City hosts teams from global enterprises (canonical hub: Delhi NCR). The curriculum covers the practical skills these teams hire for.
The programme covers the same Data Engineering with Snowflake Training curriculum delivered across India, with live online sessions, hands-on practice and career support tailored for learners in Gurgaon.
Course Overview
12-week Data Engineering with Snowflake Training: Snowpipe, Streams, dbt, Airflow, observability, cost tuning. Live labs + placement.
Why Learn Data Engineering with Snowflake Training
Indian GCC, SI and product teams actively hire data engineering professionals who can deliver from day one. This programme builds both the certification spine and the production scenarios hiring screens look for.
Who Should Join This Course
- Data engineers — Building production Snowflake pipelines.
- Analytics engineers — Adopting dbt and Snowpark patterns.
- Platform engineers — Operationalising Snowflake with Airflow.
- SnowPro Core holders — Advancing to SnowPro Advanced.
Prerequisites
SQL and Python fundamentals. Snowflake basics helpful but taught from scratch.
Learning Objectives
- Build Snowpipe Streaming pipelines
- Model medallion architectures with dbt
- Orchestrate pipelines with Apache Airflow
- Stream changes with Streams and Tasks
- Monitor cost, performance and freshness
- Pass SnowPro Advanced mapped mocks
Tools and Technologies
Snowflake, Snowpipe, dbt, Apache Airflow, Apache Kafka, Snowpark, Streamlit in Snowflake.
Career Opportunities After This Programme
- Data Engineer
- Analytics Engineer
- Big Data Engineer
- Cloud Data Engineer
- Lakehouse Architect
Hands-on Labs and Capstone
Capstone: Build an end-to-end medallion pipeline on Snowflake: ingest Kafka CDC via Snowpipe Streaming into bronze, transform with dbt into silver and gold, orchestrate Airflow DAGs, monitor freshness and cost, and ship a Streamlit in Snowflake app for stakeholders.
Production scenario: A nightly Airflow DAG misses the SLA. Switch to Snowpipe Streaming, redesign tasks as a DAG with explicit retries and parent-child dependencies, add freshness checks via dbt tests and add a PagerDuty alert.
Course Duration, Mode and Certification
The course runs for 12 weeks (72 hours). Modes: Classroom / Live Online / Hybrid. Certifications mapped: SnowPro Advanced – Data Engineer (mapped), SkilBrill Certificate.
Why Train at SkilBrill
SkilBrill Training Institute in Thoraipakkam, Chennai focuses on making you employable. Trainers are working professionals, practice mirrors real job environments, and the placement cell connects eligible candidates with hiring companies. Fee: ₹45,000 – ₹75,000. Enquire on +91 8610964691.
Career and Job Support
- Resume assistance tailored to Data Engineering roles
- LinkedIn profile rewrite and recruiter outreach
- Mock interviews with production failure scenarios
- Capstone project explanation preparation
- Placement assistance with 200+ hiring partners
- Typical salary band after completion: ₹6 – 18 LPA
Frequently Asked Questions
What is Data Engineering with Snowflake Training at SkilBrill?
A 12-week (72-hour) SnowPro Advanced mapped programme covering Snowpipe, Streams, dbt, Airflow, observability and cost optimisation on Snowflake.
Who should take this course?
Data engineers building production pipelines, analytics engineers adopting dbt, platform engineers and SnowPro Core holders advancing to SnowPro Advanced.
Do I need prior Snowflake experience?
SQL and Python fundamentals. Snowflake basics are taught from scratch where needed.
Does this prepare me for SnowPro Advanced?
Yes. SnowPro Advanced – Data Engineer is mapped with dedicated mocks.
Which tools are covered?
Snowflake, Snowpipe, dbt, Apache Airflow, Apache Kafka, Snowpark and Streamlit in Snowflake.
Is the training online or classroom?
Both, plus hybrid. Classroom is at SkilBrill Thoraipakkam, Chennai 600097.
What is the salary outlook?
Snowflake data engineers earn ₹6 – 18 LPA. Call +91 8610964691.
How do I enrol?
Call +91 8610964691 or WhatsApp 918610964691.