Data Engineering

What is Data Engineering?

Data engineers focus on building and maintaining systems that allow data collection, storage, and analysis. They are responsible for creating data pipelines, ensuring data is clean, and enabling data scientists or analysts to access and work with the data. They use tools like Apache Hadoop, Apache Spark, and various database systems (SQL/NoSQL) to build the infrastructure that supports data analysis and processing.

Apache Hadoop Apache Spark SQL Databases NoSQL Databases

What will be the outcome of this Course?

Industry-Ready Skills

Get hands-on experience with industry tools & technologies.

Career Growth

Progress from junior to senior data engineering roles.

Competitive Edge

Gain expertise in cloud, ML, and real-time processing.

Job Market Ready

Build a portfolio of projects to showcase technical abilities.

Course Objectives

Develop Industry-Ready Data Engineering Skills

Equip learners with hands-on experience in SQL, NoSQL, Python, ETL frameworks, and cloud databases to prepare them for real-world data engineering roles.

Design, Build, and Optimize Scalable Data Pipelines

Enable students to architect and implement batch and real-time data pipelines using tools like Apache Airflow, Spark, Kafka, and cloud-based ETL solutions while ensuring performance optimization.

Master Data Storage, Processing, and Governance

Teach students how to work with Data Warehouses, Data Lakes, and NoSQL systems, ensuring data quality, security, and governance in compliance with industry standards.

Associate Level Course (Data Engineering)

Focus: Introduces fundamental concepts, tools, and skills needed to step into data engineering.

Data Engineering Overview: Understand the role, responsibilities, and differences from data science.
Database Basics: Learn relational databases, SQL operations, and NoSQL fundamentals.
Data Formats & Storage: Explore CSV, JSON, Parquet, data structures, and compression.
ETL/ELT Basics: Extract, transform, and load data from simple sources.
Python for Data Engineering: Practice with Python, pandas, file handling, and automation like 'Cron'.
Data Warehousing: Understand schemas, dimensional modeling, and cloud data warehouses.
Artificial Intelligence: Understand usage of AI in data engineering.

Professional Level (Data Engineering)

Focus: Equip learners with real-time processing, cloud-native solutions, governance, and observability.

Crash Course on Associate Level : A two to three classes of the Associate level course to lay a foundation for the Professional level course.
Pipeline Orchestration: Build and manage data workflows with tools like Apache Airflow or Prefect.
Cloud Platforms: Learn cloud fundamentals across AWS, GCP, and Azure, including storage and compute services
Data Lakes & Lake-houses: Explore architectures combining raw and structured data handling (Delta Lake, Iceberg).
Advanced SQL: Master window functions, query optimization, indexing, and materialized views for performance.
Real-time Processing: Implement streaming data pipelines using Kafka, Spark, and Flink.
Cloud-Native Engineering: Deep dive into cloud ETL tools, infrastructure-as-code, and CI/CD automation
Governance & Security: Ensure data quality, lineage, access control, and regulatory compliance.
Monitoring & Observability: Set up alerts, logs, and dashboards for robust pipeline monitoring.
Capstone Project: Apply all concepts in a real-world project covering batch + stream processing, cloud deployment, and documentation

Crash Course (Data Engineering)

This crash course offers a fast-paced, hands-on introduction to modern data engineering. In just six sessions, learners will gain practical exposure to key tools, concepts, and workflows used in real-world data pipelines. Designed for aspiring data professionals, this course bridges the gap between theory and implementation.

Hands-on Skill Building – Practical experience with real tools, code, and cloud environments.
Accelerated Learning Path – Compressed timeline tailored for professionals and fast learners.
Industry-Relevant Exposure – Aligned with current job market needs in data engineering roles.
Career Transition Ready – Equips participants with the confidence and language to pursue data engineering roles or projects.

Foundations of Data Engineering
Understand data engineering roles, data lifecycle, and the modern data ecosystem.
Working with Databases
Learn SQL basics, relational vs NoSQL concepts, and data modeling essentials.
Data Formats & Processing
Handle CSV, JSON, Parquet, and compressed data formats using
Python and CLI.ETL Pipeline Design
Build lightweight pipelines: extract from APIs, transform with Python, and load into databases. Scheduling & Automation
Automate tasks with Cron and understand basic pipeline orchestration logic.
Cloud & Warehousing Essentials
Get introduced to Snowflake, BigQuery, and Redshift, with practical use cases.

What is Data Engineering?

What will be the outcome of this Course?

Industry-Ready Skills

Career Growth

Competitive Edge

Job Market Ready

Course Objectives

Develop Industry-Ready Data Engineering Skills

Design, Build, and Optimize Scalable Data Pipelines

Master Data Storage, Processing, and Governance

Course Levels (Data Engineering)

$149.00

Associate Level Course

Introduction to databases, basic data pipelines, data warehouse and data transformation techniques.

$149.00

Professional Level Course

Advanced topics such as real-time processing, distributed data systems, and machine learning pipelines.

$149.00

Crash Course

Master Real-World Data Engineering Skills
Fast — Tools, Pipelines, Cloud, and
Confidence.

Associate Level Course (Data Engineering)

Professional Level (Data Engineering)

Crash Course (Data Engineering)

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Data Engineering

What is Data Engineering?

What will be the outcome of this Course?

Industry-Ready Skills

Career Growth

Competitive Edge

Job Market Ready

Course Objectives

Develop Industry-Ready Data Engineering Skills

Design, Build, and Optimize Scalable Data Pipelines

Master Data Storage, Processing, and Governance

Course Levels (Data Engineering)

$149.00

Associate Level Course

Introduction to databases, basic data pipelines, data warehouse and data transformation techniques.

$149.00

Professional Level Course

Advanced topics such as real-time processing, distributed data systems, and machine learning pipelines.

$149.00

Crash Course

Master Real-World Data Engineering Skills Fast — Tools, Pipelines, Cloud, and Confidence.

Associate Level Course (Data Engineering)

Professional Level (Data Engineering)

Crash Course (Data Engineering)

Quick Link

Contact

Gallery

Newsletter

Master Real-World Data Engineering Skills
Fast — Tools, Pipelines, Cloud, and
Confidence.