AI-Powered Snowflake Data Engineering with Modern Data Stack
The AI-Powered Snowflake Data Engineering with Modern Data Stack program is designed to help learners build strong expertise in modern cloud-based data engineering practices used by leading organizations today. This course provides a comprehensive learning path covering the complete data engineering lifecycle — from data ingestion and transformation to building scalable data pipelines and analytics-ready datasets.
In today’s data-driven world, organizations rely on modern data platforms such as Snowflake, Databricks, and cloud-based data integration tools to process large volumes of data efficiently. This course focuses on developing practical skills using industry-standard technologies including SQL, Python, PySpark, DBT, Matillion, Azure Data Factory (ADF), and Databricks, with Snowflake as the central data warehouse platform.
Learners will gain hands-on experience in building end-to-end data pipelines, working with structured and semi-structured data, and implementing modern data transformation workflows using the Modern Data Stack approach.
The course also introduces AI-powered concepts in data engineering, helping students understand how artificial intelligence can assist in data processing, automation, optimization, and intelligent data workflows.
Throughout the program, students will work on real-world scenarios and projects that simulate how data engineers design and manage data platforms in modern enterprises. The curriculum is structured to help learners move from foundational concepts to advanced data engineering implementations, preparing them for roles such as Snowflake Data Engineer, Cloud Data Engineer, and Modern Data Platform Engineer.
By the end of the course, participants will be able to:
Design and build scalable data pipelines
Work with Snowflake cloud data warehouse effectively
Perform data transformation and modeling using DBT
Process large-scale data using Python and PySpark
Build modern ETL/ELT pipelines using Matillion and Azure Data Factory
Work with Databricks for big data processing and analytics
Understand AI-driven approaches in modern data engineering workflows
This program is ideal for aspiring Data Engineers, Data Analysts, software professionals, and anyone looking to transition into modern cloud-based data engineering roles.
Start Date & End Date
1 Subject
7 Exercises • 14 Learning Materials
7 Courses • 682 Students
Sagar is a seasoned Data Engineer with over 8 years of experience in designing, developing, and optimizing cloud-based data solutions. His expertise spans across Snowflake, Azure, AWS, and Matillion, enabling businesses to build efficient, scalable, and high-performance data pipelines.
With a deep understanding of data warehousing, ETL workflows, and cloud data engineering, Sagar has successfully led multiple end-to-end data migration and transformation projects across industries. His passion for data-driven solutions and hands-on experience with modern cloud technologies make him an invaluable mentor and instructor.
🔹 Key Expertise:
✔ Snowflake – Data warehousing, Snowpark, performance tuning
✔ Azure & AWS – Cloud data solutions, storage, and compute optimization
✔ Matillion & DBT – ETL/ELT pipeline development, orchestration, and automation
✔ Python & SQL – Data transformation, scripting, and process automation
Sagar's real-world experience and ability to simplify complex data concepts make him an ideal mentor for aspiring data engineers.
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