Online Course Certified Big Data Engineer

Certificate in Big Data Engineer

Rs.6500 Rs.3250

50% Discount will end in

To build expertise in designing, developing, and managing scalable big data systems using modern tools and frameworks for large-scale data processing and real-time analytics.

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Description

Certification Name: Certificate in Big Data Engineer

Course Id: CBDE/Q0001.

Eligibility: Graduation or Equivalent.

Objective: The Certified Big Data Engineer course is designed to equip learners with the skills and knowledge required to design, develop, manage, and optimize big data systems and solutions. The course covers a wide spectrum of big data technologies and architectures, focusing on handling large-scale data processing, storage, and real-time analytics. Participants will gain in-depth understanding of Hadoop ecosystem (HDFS, MapReduce, Hive, Pig), Apache Spark, Kafka, NoSQL databases (e.g., HBase, MongoDB, Cassandra), and cloud-based big data services (AWS, Azure, GCP).

Duration: Three Month.

πŸŽ“ How to Enroll and Get Certified in Your Chosen Course:

βœ”οΈ Step 1: Choose the course you wish to get certified in.

βœ”οΈ Step 2: Click on the β€œEnroll Now” button.

βœ”οΈ Step 3: Proceed with the enrollment process.

βœ”οΈ Step 4: Enter your billing details and continue to course fee payment.

βœ”οΈ Step 5: You will be redirected to the payment gateway. Pay the course and exam fee using one of the following methods:
Debit/Credit Card, Wallet, Paytm, Net Banking, UPI, or Google Pay.

βœ”οΈ Step 6: After successful payment, you will receive your study material login ID and password via email within 48 hours of fee payment.

βœ”οΈ Step 7: Once you complete the course, take the online examination.

βœ”οΈ Step 8: Upon passing the examination, you will receive:
β€’ A soft copy (scanned) of your certificate via email within 7 days of examination.
β€’ A hard copy (original with official seal and signature) sent to your address within 45 day of declaration of result.

βœ”οΈ Step 9: After certification, you will be offered job opportunities aligned with your area of interest.

Online Examination Detail:

Duration- 60 minutes.
No. of Questions- 30. (Multiple Choice Questions).
Maximum Marks- 100, Passing Marks- 40%.
There is no negative marking in this module.

Marking System:
S.No. No. of Questions Marks Each Question Total Marks
1 10 5 50
2 5 4 20
3 5 3 15
4 5 2 10
5 5 1 5
30 100
How Students will be Graded:
S.No. Marks Grade
1 91-100 O (Outstanding)
2 81-90 A+ (Excellent)
3 71-80 A (Very Good)
4 61-70 B (Good)
5 51-60 C (Average)
6 40-50 P (Pass)
7 0-40 F (Fail)

🌟 Key Benefits of Certification- Earning a professional certification not only validates your skills but also enhances your employability. Here are the major benefits you gain:

βœ… Practical, Job-Ready Skills – Our certifications are designed to equip you with real-world, hands-on skills that match current industry demands β€” helping you become employment-ready from day one.

πŸ“œ Lifetime Validity – Your certification is valid for a lifetime β€” no renewals or expirations. It serves as a permanent proof of your skills and training.

πŸ” Lifetime Certificate Verification – Employers and institutions can verify your certification anytime through a secure and reliable verification system β€” adding credibility to your qualifications.

🎯 Industry-Aligned Certification –All certifications are developed in consultation with industry experts to ensure that what you learn is current, relevant, and aligned with market needs.

πŸ’Ό Preferred by Employers – Candidates from ISO-certified institutes are often prioritized by recruiters due to their exposure to standardized, high-quality training.

🀝 Free Job Assistance Based on Your Career Interests – Receive personalized job assistance and career guidance in your preferred domain, helping you land the right role faster.

Assessment Modules:

Module 1: Introduction to Big Data and Hadoop Ecosystem: Understanding Big Data and its characteristics, Types of data: Structured, Semi-structured, Unstructured, Introduction to Hadoop and HDFS, Hadoop architecture and components, Setup and configuration of Hadoop cluster, Use cases and applications of Big Data.

Module 2: Hadoop Distributed File System (HDFS) and MapReduce: Working with HDFS and its commands, File read/write operations in HDFS, Introduction to MapReduce programming, MapReduce job lifecycle and data flow, Writing and executing MapReduce programs, Use of combiners, partitioners, and counters in MapReduce.

Module 3: Apache Hive and Pig: Hive architecture and components, Creating databases, tables, and partitions in Hive, HiveQL for querying large datasets, Introduction to Pig and its data model, Writing Pig Latin scripts for data transformation, Hive vs Pig – differences and use cases.

Module 4: Apache Spark for Big Data Processing: Introduction to Spark architecture and RDDs, Spark SQL and DataFrames, Spark Streaming and real-time data processing, Machine learning with MLlib in Spark, Integrating Spark with Hadoop ecosystem, Performance tuning and optimization in Spark.

Module 5: NoSQL Databases for Big Data: Understanding NoSQL and its types (Key-value, Document, Column, Graph), Working with HBase – data model and shell commands, CRUD operations in HBase, Introduction to MongoDB and basic operations, Indexing and aggregation in MongoDB, Use cases of NoSQL in Big Data.

Module 6: Data Ingestion, Workflow Management and Project Deployment: Data ingestion tools: Apache Sqoop and Flume, Real-time data ingestion with Kafka, Introduction to workflow management using Apache Oozie and Airflow, Monitoring and debugging data pipelines, Big Data project lifecycle and deployment strategies, Capstone project with end-to-end Big Data pipeline development.

Career Options After Certificate in Big Data Engineer (India)

1. Big Data Engineer

Role & Responsibilities

  • Design, develop, and maintain big data pipelines

  • Work with Hadoop, Spark, Kafka, and other big data technologies

  • Integrate and process large volumes of structured and unstructured data

  • Optimize performance, reliability, and scalability of data systems

Industries
IT & software services, product companies, e-commerce, BFSI, analytics firms

Salary Range

  • Entry level: β‚Ή7 – β‚Ή12 LPA

  • Experienced: β‚Ή12 – β‚Ή25 LPA

2. Hadoop Developer

Role & Responsibilities

  • Develop distributed applications using Hadoop ecosystem

  • Write MapReduce programs and work with HDFS

  • Support data processing and analytics pipelines

Industries
IT services, product companies, cloud platforms

Salary Range

  • β‚Ή6 – β‚Ή15 LPA

3. Spark Developer

Role & Responsibilities

  • Build real-time and batch processing pipelines with Apache Spark

  • Process and analyze large-scale datasets

  • Integrate Spark with Hadoop, Kafka, or cloud platforms

Industries
E-commerce, IT services, fintech, analytics companies

Salary Range

  • β‚Ή8 – β‚Ή18 LPA

4. Big Data Analyst

Role & Responsibilities

  • Analyze big data for business insights

  • Work with visualization and reporting tools

  • Support decision-making for operations, marketing, and finance

Industries
Retail, BFSI, IT, consulting, e-commerce

Salary Range

  • β‚Ή6 – β‚Ή14 LPA

5. Data Engineer (Big Data Focus)

Role & Responsibilities

  • Build and manage large-scale data pipelines

  • Work with ETL, cloud data warehouses, and big data frameworks

  • Ensure high-quality, reliable, and accessible data

Industries
IT services, startups, analytics firms, product companies

Salary Range

  • β‚Ή7 – β‚Ή20 LPA

6. Cloud Big Data Engineer

Role & Responsibilities

  • Implement big data solutions on cloud platforms (AWS, Azure, GCP)

  • Optimize data processing, storage, and analytics in cloud environments

  • Ensure data security, compliance, and performance

Industries
Cloud service providers, IT companies, fintech

Salary Range

  • β‚Ή10 – β‚Ή25 LPA

7. Big Data Consultant

Role & Responsibilities

  • Advise organizations on big data strategy and architecture

  • Evaluate big data tools and technologies

  • Design scalable data systems and analytics workflows

Industries
Consulting firms, IT services, product companies

Salary Range

  • β‚Ή12 – β‚Ή30 LPA

8. Freelance / Contract Big Data Engineer

Role & Responsibilities

  • Develop big data pipelines and analytics solutions for clients

  • Work on Hadoop, Spark, and cloud projects on a contractual basis

Earning Potential

  • β‚Ή50,000 – β‚Ή3,00,000+ per month (project-based)

Industry Demand in India

Big Data Engineers are in high demand across:

  • IT & Software Services

  • Product-Based & SaaS Companies

  • BFSI & Fintech

  • E-commerce & Retail Analytics

  • Cloud & Data Platforms

  • AI, ML, and Data Science Projects

Career Growth Path

  • Entry Level: Junior Big Data Engineer, Hadoop Developer

  • Mid Level: Big Data Engineer, Spark Developer, Data Engineer

  • Senior Level: Cloud Big Data Engineer, Big Data Architect, Analytics Lead

  • Leadership: Head of Data Engineering, Chief Data Officer (CDO)

Key Skills Gained from the Certification

  • Hadoop ecosystem: HDFS, MapReduce, Hive, Pig

  • Apache Spark and real-time processing

  • Kafka & streaming data integration

  • Data storage, ETL, and pipeline design

  • Cloud platforms: AWS, Azure, GCP

  • SQL, NoSQL, and data governance

Key Takeaway

The Certificate in Big Data Engineer equips professionals with high-demand skills to manage, process, and analyze massive datasets. With India’s data-driven economy growing rapidly, certified Big Data Engineers enjoy strong salary packages, multiple career paths, and global job opportunities.