Data Engineering is the process of designing, building, and managing data infrastructure and pipelines to collect, store, and process large volumes of data efficiently. It supports data analysis, machine learning, and business intelligence by ensuring data is clean, accessible, and reliable. With the growth of big data, IoT, and AI, data engineering has become a critical role in modern organizations.
Course OutlineLearn data systems, change tracking, ETL/ELT pipelines, OLAP vs. OLTP, and dimensional modeling using tools like Python, Talend, Kafka, and Airflow.
Master Python essentials for data engineering, including data manipulation, scripting, and automation for building robust data pipelines and processing workflows.
Learn to write efficient SQL scripts for data extraction, transformation, and loading (ETL), create complex queries, and optimize databases for engineering workflows.
Clean, structure, and enrich raw datasets using Python and SQL to prepare data for analytics and machine learning applications.
Understand cloud fundamentals and deploy data solutions on platforms like AWS or GCP with services for storage, compute, and scalability.
Learn to create interactive dashboards and visualizations in Tableau to effectively communicate data insights and support decision-making.
Build real-time data pipelines using tools like Apache Kafka and Spark Streaming for fast, scalable data processing.
Automate and schedule ETL workflows using Apache Airflow and other orchestration tools for reliable, hands-free data operations.
Apply your skills on industry-grade projects and receive personalized mentorship to build your portfolio.
Prepare for job interviews. Guidance on next steps and internship opportunity at Discover the Tech
Start your journey to a global career in Data Engineering! Gain hands-on skills and become an industry-ready professional