Data Engineering Capstone Project
Apply your skills in this hands-on data engineering capstone project designed to simulate real-world data infrastructure challenges. This course is ideal for learners who want to consolidate their knowledge of big data pipelines, cloud platforms, and data architecture by completing a comprehensive, end-to-end engineering project.
What You’ll Learn
- Designing scalable data pipelines using tools like Apache Spark, Kafka, and Airflow
- Building data lakes and warehouses using platforms such as AWS, GCP, or Azure
- ETL/ELT development, data ingestion strategies, and orchestration workflows
- Real-time and batch data processing techniques
- Data quality monitoring, testing, and documentation best practices
- Deploying solutions using Docker and Kubernetes
- Visualizing results with tools like Tableau or Power BI
Requirements
- Completion of foundational courses in data engineering or related fields
- Proficiency in Python, SQL, and basic understanding of cloud computing
- Experience with data pipeline tools is recommended
Course Description
This data engineering capstone project offers learners an opportunity to implement all the skills acquired through their training into a full-scale data engineering solution. You will architect, develop, and deploy a robust data pipeline that ingests raw data, transforms it, and loads it into a well-structured and query-optimized data warehouse or data lake.
Throughout the course, you’ll tackle real-world data engineering challenges, such as handling semi-structured and unstructured data, ensuring pipeline resilience, and monitoring data quality. This capstone also encourages the use of CI/CD practices and containerization, equipping you with the modern DevOps practices necessary in today’s tech landscape.
Upon completion, you’ll have a portfolio-ready project that demonstrates your ability to build and maintain production-grade data systems, making you stand out to employers and clients.
About the Instructor
The capstone project is developed by industry professionals and senior data engineers with years of experience designing scalable data architectures for large-scale enterprises. Their mentorship ensures practical, relevant, and industry-aligned outcomes.
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- Data Engineering with Apache Spark
- Introduction to Big Data
- Cloud Data Platforms (AWS/GCP/Azure)
- Data Pipeline Orchestration with Airflow
- Data Analytics and Visualization
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