Description
Certification Name: Certificate in Data Engineer
Course Id: CDE/Q0001.
Eligibility: Graduation or Equivalent.
Objective: The Certified Data Engineer course is designed to equip professionals with the technical expertise required to design, build, manage, and optimize scalable data pipelines and infrastructure for data collection, storage, processing, and analysis. The course covers the full data engineering lifecycle, including data modeling, ETL/ELT processes, data warehousing, and big data processing frameworks such as Apache Spark, Hadoop, and Kafka.
Duration: Three Month.
How to Enroll and Get Certified in Your Chosen Course:
Step 1: Choose the course you wish to get certified in.
Step 2: Click on the “Enroll Now” button.
Step 3: Proceed with the enrollment process.
Step 4: Enter your billing details and continue to course fee payment.
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.
Step 6: After successful payment, you will receive your study material login ID and password via email within 48 hours of fee payment.
Step 7: Once you complete the course, take the online examination.
Step 8: Upon passing the examination, you will receive:
• A soft copy (scanned) of your certificate via email within 7 days of examination.
• A hard copy (original with official seal and signature) sent to your address within 45 day of declaration of result.
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:
Practical, Job-Ready Skills – Our certifications are designed to equip you with real-world, hands-on skills that match current industry demands — helping you become employment-ready from day one.
Lifetime Validity – Your certification is valid for a lifetime — no renewals or expirations. It serves as a permanent proof of your skills and training.
Lifetime Certificate Verification – Employers and institutions can verify your certification anytime through a secure and reliable verification system — 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.
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: Data Engineering Fundamentals: Introduction to Data Engineering and Lifecycle, Data Types and Sources (Structured, Semi-structured, Unstructured), Data Formats (CSV, JSON, Parquet, Avro), Basics of Data Modeling and Schemas, Understanding ETL vs ELT Processes, Overview of Data Engineering Tools and Ecosystem.
Module 2: Relational and Non-Relational Databases: Designing Relational Databases (ER Models, Normalization), SQL for Data Manipulation and Query Optimization, Introduction to NoSQL Databases (Key-Value, Document, Column-Family, Graph), Hands-on with MongoDB and Cassandra, Indexing and Partitioning Strategies, Data Warehousing Concepts (Star/Snowflake Schema).
Module 3: Data Pipeline Development: Introduction to Batch and Stream Data Pipelines, ETL Development using Apache NiFi and Talend, Real-time Data Ingestion with Apache Kafka and Flume, Data Processing with Apache Spark and Spark SQL, Workflow Orchestration using Apache Airflow, Monitoring and Logging Data Pipelines.
Module 4: Big Data Technologies: Hadoop Ecosystem and HDFS Architecture, Data Processing using MapReduce and YARN, Apache Hive and Pig Basics, Introduction to Distributed Computing with Spark, Handling Large Datasets using Dask, Performance Tuning in Big Data Environments.
Module 5: Cloud Data Engineering: Cloud Platforms Overview (AWS, GCP, Azure), Cloud Storage (S3, Google Cloud Storage, Azure Blob), Managed Databases and Warehousing (Redshift, BigQuery, Snowflake), Building Data Pipelines using Cloud Services (AWS Glue, GCP Dataflow), Infrastructure as Code (Terraform, CloudFormation), Cloud Data Security and Compliance.
Module 6: Data Governance, Security & Real-world Projects: Data Quality and Lineage, Metadata Management Tools (Apache Atlas, DataHub), Data Security (Encryption, Access Control, Role Management), Compliance (GDPR, HIPAA), Capstone Project: Building Scalable Data Engineering Pipeline, Industry Use Cases and Best Practices in Data Engineering.
Career Options After Certificate in Data Engineer (India)
1. Data Engineer
Role & Responsibilities
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Design, build, and maintain data pipelines
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Work with ETL (Extract, Transform, Load) processes
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Integrate structured and unstructured data from multiple sources
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Ensure data quality, security, and accessibility for analytics
Industries
IT services, product companies, BFSI, e-commerce, analytics firms
Salary Range
-
Entry level: ₹6 – ₹10 LPA
-
Experienced: ₹12 – ₹22 LPA
2. Big Data Engineer
Role & Responsibilities
-
Work with big data technologies like Hadoop, Spark, and Kafka
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Handle large-scale data storage, processing, and transformation
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Optimize big data workflows and pipelines
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Support analytics and machine learning teams
Industries
IT companies, analytics firms, telecom, e-commerce
Salary Range
-
₹8 – ₹20 LPA
3. ETL Developer
Role & Responsibilities
-
Build ETL workflows for data extraction, transformation, and loading
-
Maintain and optimize data integration pipelines
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Work with SQL, Python, or data integration tools
-
Ensure timely and accurate data delivery to business teams
Industries
Banks, insurance, IT, product companies
Salary Range
-
₹6 – ₹15 LPA
4. Cloud Data Engineer
Role & Responsibilities
-
Manage cloud-based data pipelines and storage
-
Work with platforms like AWS, Azure, or GCP
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Implement security, scaling, and monitoring for cloud data
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Support cloud analytics and data warehousing
Industries
Cloud service providers, IT, product startups
Salary Range
-
₹10 – ₹22 LPA
5. Data Warehouse Engineer
Role & Responsibilities
-
Design, implement, and maintain data warehouses
-
Support business intelligence and reporting teams
-
Ensure efficient storage, retrieval, and transformation of data
Industries
Retail, BFSI, IT services, consulting firms
Salary Range
-
₹8 – ₹18 LPA
6. Analytics Engineer / Data Pipeline Engineer
Role & Responsibilities
-
Prepare data for analytics and BI solutions
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Build pipelines that support dashboards, reports, and ML models
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Collaborate with data scientists and business analysts
Industries
Product companies, startups, analytics firms
Salary Range
-
₹7 – ₹16 LPA
7. Data Platform Engineer
Role & Responsibilities
-
Maintain scalable data platforms for large organizations
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Implement storage, ETL, streaming, and data integration
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Ensure system reliability and performance
Industries
IT services, e-commerce, BFSI, cloud platforms
Salary Range
-
₹12 – ₹25 LPA
8. Freelance / Contract Data Engineer
Role & Responsibilities
-
Build and maintain data pipelines for clients
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Work on cloud, analytics, and automation projects
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Support startups or enterprises on-demand
Earning Potential
-
₹50,000 – ₹2,50,000+ per month (project-based)
Industry Demand in India
Data Engineers are in high demand across:
-
IT & Software Services
-
Product-Based & SaaS Companies
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Banking, Finance & Insurance
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E-commerce & Retail Analytics
-
Cloud & Data Platforms
-
AI, ML & Big Data Projects
Career Growth Path
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Entry Level: Junior Data Engineer, ETL Developer
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Mid Level: Data Engineer, Analytics Engineer
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Senior Level: Big Data Engineer, Cloud Data Engineer, Data Platform Lead
-
Leadership: Head of Data Engineering, Chief Data Officer (CDO)
Key Skills Gained from the Certification
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SQL & NoSQL databases
-
ETL and data pipeline development
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Big data tools: Hadoop, Spark, Kafka
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Cloud platforms: AWS, Azure, GCP
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Data warehousing & BI support
-
Python or other scripting for data workflows
Key Takeaway
The Certificate in Data Engineer equips learners with high-demand skills for building, managing, and optimizing data pipelines. With India’s growing focus on data-driven decision-making, certified professionals can access well-paying roles, fast career growth, and freelance opportunities in analytics and cloud projects.
