Big Data Engineering Course in Chennai
825 Ratings
Build expertise in large-scale data processing with Edubrights' Big Data Engineering Course in Chennai. Designed for students, freshers, job seekers, and working professionals, this training program helps you develop practical skills in big data technologies, distributed computing, data pipelines, and data management through hands-on learning and real-world projects.
Learn how organizations process massive volumes of structured and unstructured data to support analytics, business intelligence, and data-driven decision-making. Through practical assignments, industry-focused case studies, and project-based training, you will gain the knowledge needed to design, manage, and optimize modern big data solutions.
Key Highlights:
✅ Real-Time Big Data Engineering Projects and Industry Case Studies
✅ Hands-On Training in Distributed Data Processing and Data Pipelines
✅ Data Ingestion, Transformation, and Large-Scale Data Management Concepts
✅ Practical Exposure to Big Data Architecture and Engineering Workflows
✅ Industry-Aligned Curriculum Designed by Experienced Data Engineers
✅ Certification Guidance and Career Development Support
✅ Resume Building, Mock Interviews, and Placement Assistance
✅ Flexible Online, Classroom, and Weekend Training Options
Start your Big Data Engineering journey with Edubrights and gain the practical skills, project experience, and industry knowledge needed to become a job-ready Big Data Engineer in today's data-driven technology landscape.
Call Course Advisor
₹30000
₹45000
Case Studies and Projects
2+
Hours of Training
20+
Placement Assurance
100%
Expert Support
Yes
Support & Access
Lifetime
Certification
Yes
Skill Level
All
Language
All
Course Objectives
1.What exactly Big Data Engineering training cover?
The training covers data collection, cleaning, visualization, statistical modeling, machine learning, and big data technologies to extract valuable insights from complex datasets.
2. What are the main objectives of the Big Data Engineering course for your development skills?
To develop practical skills in data analysis, predictive modeling, data visualization, and decision-making that drive business solutions.
Design Scalable Distributed Architectures
Master the architectural layout of distributed file systems and massive multi-node environments to store petabytes of structural and non-structural digital information.
Build High-Throughput ETL Pipelines
Gain the exact expertise required to extract, clean, transform, and load massive data sets efficiently using localized batch scripts and parallel execution
Popular Techniques Covered in This Course
1.Data ingestion and ETL pipelines
2.Hadoop and Spark fundamentals
3.NoSQL and SQL database design
4.Cloud data architecture
5.Data orchestration and automation
6.Data modeling and governance
7.Distributed storage
8.Python for big data
9.Real-time data streaming (Kafka)
10.Data security and compliance
Get Hands-on Knowledge about Real-Time Projects
Project 1
1. ETL Pipeline Design
Build and automate an Extract-Transform-Load pipeline using Hadoop and Spark to process large datasets.
Project 2
2. Real-Time Data Streaming Application
Implement a data pipeline with Apache Kafka and Spark Streaming to analyze live data and generate insights.
Project 3
3. Healthcare NoSQL Data Lake Consolidation
Design a multi-source data consolidation repository built to ingest patient medical record details, diagnostic histories, and unformatted textual health reports. You will schema-model this unstructured information across scalable, distributed wide-column NoSQL databases to support rapid queries.
Project 4
4. Enterprise Airflow Pipeline Orchestration System
Develop a fault-tolerant workflow orchestrator utilizing Apache Airflow to handle multi-stage data jobs. You will build complex Directed Acyclic Graphs (DAGs) that check for incoming database dumps, trigger analytical compute tasks, verify schema compliance, and update executive databases.
Project 5
5. Serverless Cloud Data Warehouse Migration
Architect a secure cloud data infrastructure strategy to migrate traditional on-premises infrastructure databases into a cloud environment. You will program automated pipelines that handle massive historical loads, enforce end-to-end data encryption, and optimize cloud data partitions to significantly reduce operational costs.
Key Features
Edubrights offers Big Data Engineering Training in virtual mode with expert trainers. Here are the key features.
40 Hours Course Duration
100% Job Oriented Training
Industry Expert Faculties
Free Demo Class Available
Completed 500+ Batches
Certification Guidance
Curriculum
Module 1: Data Engineering Basics
- Introduction to data lifecycle
- Data engineering vs. data science vs. analytics
- Big Data characteristics
Module 2: Programming Foundations
- Python for data manipulation
- Linux fundamentals
- Shell scripting
Module 3: Data Storage
- Relational databases (SQL)
- NoSQL databases (MongoDB, Cassandra, HBase)
- Data warehouses and data lakes
Module 4: Distributed Computing
- Hadoop ecosystem (HDFS, MapReduce, YARN)
- Spark architecture and real-time processing
Module 5: ETL and Data Pipelines
- Data ingestion and extraction
- Transformation/cleaning strategies
- Tools: Apache NiFi, Talend, Informatica
Module 6: Data Modeling & Architecture
- Schema design and normalization
- Star and snowflake schemas
- Data governance and metadata management
Module 7: Data Orchestration & Automation
- Managing data workflows with Apache Airflow
- Monitoring and scheduling pipelines
Module 8: Cloud Data Engineering
- Big data on AWS, Azure, GCP
- Cloud storage and architectures
Module 9: Data Security and Compliance
- Encryption, privacy, and access controls
- Data quality and testing
Module 10: Scalability & Performance
- Partitioning, sharding, and optimization
- Designing resilient systems
Module 11: Real-world Projects & Emerging Trends
- End-to-end pipeline implementation
- Latest trends: DataOps, serverless data processing
Receive Training From Our Skilled and Effective Trainers
Experience in the Industry Gain knowledge from experts with practical Big Data Engineering project experience in a variety of sectors.
Backgrounds at the Top Prominent corporations such as HCL, TCS, Accenture, and Cognizant employ trainers.
Clear & Effective Teaching Excellent communication and real-world examples simplify complex subjects.
Hands-On Learning Focus Students can apply their abilities in real-world situations with the use of case studies and real-time projects.
Up-to-Date Knowledge Trainers stay current with the latest tools, techniques, and best practices.
Succeed Our Resourceful Certification
Our certification validates your expertise in designing scalable data architectures, building data pipelines, and mastering distributed systems. It prepares you for real-world big data engineering roles in multiple industries.
Course FAQs
Q1: What is Big Data Engineering?
It’s the discipline of creating systems that manage, process, and analyze vast volumes of complex data efficiently.
Q2: What programming languages will I use?
Primarily Python and SQL; sometimes Java and Scala as well.
Q3: What tools and platforms are taught?
Hadoop, Spark, Airflow, Kafka, AWS, Azure, GCP, NoSQL databases.
Q4: Do I need a background in coding?
Basic coding skills help, but foundational modules are included.
Q5: What kind of projects will I build?
ETL pipelines, real-time data streaming, data warehouse solutions.
Q6: Is cloud data engineering covered?
Yes, with hands-on exposure to cloud platforms.
Q7: What industries hire Big Data Engineers?
Tech, finance, healthcare, telecom, e-commerce, and more.
Q8: How long does the course take?
Usually 4–6 months with a balanced pace.
Q9: Will I learn about real-time analytics?
Yes, including streaming with Spark and Kafka.
Q10: Is certification valuable for jobs?
Yes, it proves your expertise with top tools and systems.
Q11: Do we focus on Scala or Python when working within Apache Spark?
The primary development language utilized throughout our programming modules is Python (via PySpark). Python's readability allows us to focus heavily on learning distributed logic and performance tuning without getting bogged down in complex syntactic boilerplates.
Q12: Can a business professional with no tech experience take this training?
This is a highly technical engineering course. If you have no past exposure to programming or database infrastructure, we strongly suggest enrolling in our foundational SQL and basic Python primers before stepping into distributed cluster computing.
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