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Curriculam Designed By Experts
Expertly designed curriculum for future-ready professionals.Industry Oriented Curriculam
An exhaustive curriculum designed by our industry experts which will help you to get placed in your dream IT company-
30+  Case Studies & Projects
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9+  Engaging Projects
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10+   Years Of Experience
Fundamentals of data modeling (conceptual, logical, physical)
Data Engineering Training Projects
Become a Data Engineering Expert With Practical and Engaging Projects.- Practice essential Tools
- Designed by Industry experts
- Get Real-world Experience
Basic Data Pipeline
Build a simple ETL pipeline that extracts data from CSV files, transforms it (cleaning and formatting), and loads it into a database.
Data Warehouse Setup
Create a small data warehouse using a relational database and load sample sales data for basic querying.
Data Quality Checker
Develop a script that validates datasets for missing values, duplicates, and inconsistent formats.
Automated Data Monitoring
Build a dashboard that monitors data pipeline health and data quality metrics with alerts on failures.
Data Lake Implementation
Design and implement a data lake on cloud storage (e.g., AWS S3), organizing raw and processed data for analytics.
Streaming Data Pipeline
Set up a real-time data pipeline using Apache Kafka to ingest and process streaming data from sensors or web logs.
Scalable Big Data Pipeline
Create a distributed pipeline using Apache Spark to process large datasets and generate aggregated reports.
Machine Learning Feature Store
Develop a feature store to manage and serve machine learning features efficiently across different models.
Data Orchestration with Airflow
Implement complex data workflows and dependencies using Apache Airflow for end-to-end pipeline automation and monitoring.
Key Features
Practical Training
Global Certifications
Flexible Timing
Trainer Support
Study Material
Placement Support
Mock Interviews
Resume Building
Batch Schedule
Weekdays Regular (Class 1Hr - 1:30Hrs) / Per Session
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27 - Oct - 2025 Starts Coming Monday ( Monday - Friday) 08:00 AM (IST)
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29 - Oct - 2025 Starts Coming Wednesday ( Monday - Friday) 10:00 AM (IST)
Weekend Regular (Class 3Hrs) / Per Session
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01- Nov - 2025 Starts Coming Saturday ( Saturday - Sunday) 10:00 AM (IST)
Weekend Fast-track (Class 6Hrs - 7Hrs) / Per Session
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02 - Nov - 2025 Starts Coming Saturday ( Saturday - Sunday) 10:00 AM (IST)
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- Learning strategies that are appropriate and tailored to your company's requirements.
- Live projects guided by instructors are a characteristic of the virtual learning environment.
- The curriculum includes of full-day lectures, practical exercises, and case studies.
Data Engineering Training Overview
Goals Accomplished by Data Engineering Certification Course in Online
Online Data Engineering training Course aim to equip learners with the skills to design, build, and maintain scalable data pipelines and architectures. Participants gain proficiency in data ingestion, transformation, and storage using modern tools and platforms. These programs emphasize practical knowledge of cloud services, databases, and big data technologies. Graduates develop the ability to optimize data workflows, ensuring data quality and accessibility for analytics and machine learning. Overall, the training prepares candidates to support data-driven decision-making within organizations.
Future Career Opportunities Emerging from Data Engineering Training Course Online
- Data Engineer: Design and maintain robust data pipelines for reliable data flow and processing. Ensure data is cleaned, validated, and available for analytics or machine learning tasks.
- Big Data Engineer: Work with distributed systems like Hadoop and Spark to manage large-scale datasets. They focus on optimizing data processing speed and scalability across massive infrastructures.
- Cloud Data Engineer: Build and optimize data infrastructure using cloud platforms such as AWS, Azure, or GCP. They implement cost-effective and secure cloud-based solutions for real-time data handling.
- Data Architect: Develop blueprints for data management systems, ensuring alignment with business goals. They also set data standards, policies, and governance models across the organization.
- Machine Learning Engineer: Collaborate with data scientists by providing clean, structured data for model training. They also help in deploying and scaling models into production environments efficiently.
New Frameworks Introduced in Data Engineering Course in Online
Modern Data Engineering Training in Online incorporate frameworks such as Apache Airflow for workflow orchestration, Apache Kafka for real-time data streaming, and Apache Spark for distributed data processing. Cloud-native frameworks like AWS Glue and Google Cloud Dataflow offer serverless data integration and transformation capabilities. These frameworks enable efficient handling of big data, automation of data pipelines, and real-time analytics. Integrating these tools prepares learners for the evolving demands of data infrastructure and operational excellence in enterprises.
Trends and Essential Skills Related to Data Engineering certification in Online
- Cloud Computing Proficiency: Mastery of AWS, Azure, and Google Cloud is essential for modern data engineering roles. This enables scalable, secure, and cost-effective data infrastructure management.
- Automation and Orchestration: Skills in tools like Apache Airflow automate complex workflows, boosting efficiency. These tools help schedule, monitor, and manage data pipeline execution with ease.
- Big Data Technologies: Expertise in Hadoop, Spark, and Kafka is critical for managing large-scale data ecosystems. They enable real-time processing, distributed storage, and streaming data analysis.
- Data Modeling and Warehousing: Ability to design scalable data warehouses and optimize schemas for query performance. This ensures structured, accessible, and high-performance data retrieval for analytics.
- Programming and Scripting: Strong knowledge of Python, SQL, and Scala to build flexible and maintainable pipelines. These languages support data transformation, cleaning, and integration across systems.
Applications and Uses of Data Engineering Training in Online
Data Engineering training with Placement empowers professionals to build the backbone of data-driven organizations by enabling smooth data collection, processing, and storage. These skills are vital in industries such as finance, healthcare, retail, and technology where large volumes of data must be efficiently handled. Graduates can implement real-time analytics, support machine learning initiatives, and enhance business intelligence. The Data Engineering Certification Course in Online also helps organizations reduce data silos, improve data quality, and accelerate decision-making processes through reliable data infrastructure.
Career Opportunities After Data Engineering
Data Engineer
Designs, builds, and maintains scalable data pipelines and architectures for collecting, processing, and storing large datasets. Ensures data is accessible analysis.
Big Data Engineer
Works with distributed systems like Hadoop and Spark to handle big data storage and processing. Develops solutions for high-volume, high-velocity data environments.
Cloud Data Engineer
Implements and manages data infrastructure on cloud platforms such as AWS, Azure, or Google Cloud. Focuses on serverless data workflows and scalable cloud storage.
Data Architect
Creates data models and blueprints that define data standards and flow across systems. Aligns data infrastructure with business goals and compliance requirements.
ETL Developer
Develops extract, transform, load (ETL) processes to integrate data from multiple sources into data warehouses or lakes. Optimizes data flow for performance and accuracy.
Machine Learning Engineer
Prepares and engineers data pipelines that enable machine learning model training and deployment. Works closely with data scientists to deliver clean, usable data.
Skill to Master
SQL and NoSQL Databases
Data Warehousing Concepts
ETL Pipeline Development
Apache Hadoop Ecosystem
Apache Spark and Kafka
Cloud Platforms
Kafka & Streaming
Data Modeling and Architecture
Python and Scala Programming
Data Pipeline Orchestration
Charting and graphical representation
Big Data Processing
Tools to Master
Apache Hadoop
Apache Spark
Apache Kafka
Apache Airflow
AWS Glue
Google Cloud Dataflow
Microsoft Azure Data Factory
Snowflake
Talend
Informatica
PostgreSQL
MongoDB
Learn from certified professionals who are currently working.
Training by
Rajesh, having 8+ yrs of experience
Specialized in: Big Data Architecture and Cloud Data Engineering.
Note: Rajesh is well-known for his practical approach to integrating big data tools and mentoring students on solving complex data challenges.
We are proud to have participated in more than 40,000 career transfers globally.
Data Engineering Certification
Yes, there are multiple certifications available for data engineering, each focusing on different platforms and skill sets. Popular certifications include Google Cloud Professional Data Engineer, AWS Certified Data Analytics, Microsoft Azure Data Engineer Associate, and Databricks Certified Data Engineer.
Yes, pursuing multiple certifications is common and beneficial in the evolving data landscape. Data Engineering training with Placement broadens your expertise across platforms like AWS, Google Cloud, and Azure, and deepens your understanding of various tools and technologies.
Yes, many Data Engineering training with Placement exams are available online with remote proctoring. This allows candidates to take the exam from the comfort of their homes while maintaining exam integrity.
While real-world experience can significantly enhance your chances of securing a placement, it is not always mandatory. Many training programs offer internship opportunities and project-based learning that simulate real-world scenarios, helping you build practical skills.
Frequently Asked Questions
- Basic programming and database knowledge are recommended but beginners can join. Many courses start with foundational concepts to accommodate all levels.
- Key areas include ETL, data warehousing, big data tools, and cloud platforms.
- It also covers data pipeline design and real-time processing techniques
- Students complete hands-on projects based on real-world datasets.
- Portfolio reviews and guidance help showcase skills effectively.
- Yes, you get a certificate validating your skills and course completion. Certificates often help in job applications and career advancement.
- Roles like Data Engineer, Big Data Developer, and Data Pipeline Architect are common.
- Opportunities also exist in cloud data services and analytics engineering.