Azure Data Engineer
Learning Format
Online Mode
Total Training Duration
180 Hrs
Duration
4 Month
Certification
Yes
Azure Data Engineering Course in PCMC Pune
Advance your career in cloud and data technologies with the Azure Data Engineering Course in PCMC Pune. This course is ideal for tech enthusiasts, freshers, and IT professionals who want to specialize in Microsoft Azure’s powerful cloud ecosystem. You will gain practical skills in building, managing, and optimizing modern data systems using Azure tools such as Data Factory, Synapse Analytics, and Databricks.
The program combines theory with hands-on labs and real-time projects. You’ll learn essential skills, including data ingestion, transformation, storage, and big data analytics. These projects mirror real-world challenges, preparing you to design scalable, efficient data pipelines that meet industry standards.
As a leading Online Software Training Institute in PCMC Pune, IntelliBI Innovations Technologies also offers courses like the Generative AI Course in PCMC Pune, giving you the chance to expand your expertise in emerging AI technologies. This ensures you stay ahead in cloud computing and intelligent automation.
Trainers with extensive industry experience guide you through best practices, tools, and certification preparation, helping you become a job-ready professional. By the end of the course, you will have a portfolio of projects showcasing your ability to handle complex data engineering tasks.
Join the Azure Data Engineering Course and take the first step toward a successful career in cloud data management.
Course Summary
Eligibility
Tech & Non-Tech Working professional, Freshers, Graduate from any domain.
Real time projects
Gain hands-on experience through projects that simulate real-world challenges, preparing you for a career in analytics.
Dedicated Profile Building
Along with learning, we help you with ATS resume building and LinkedIn profile optimization
Hands-on Industry Relevant Casestudies
Complete guidance for 25+ Assignments and case studies to help you gain the hands-on experience.
Live Doubt Solving
Get your queries solved with daily dedicated doubts solving sessions.
800+ Companies
Connect with top employers
Certification
10+ ISO Globally recognized certified
LMS Access for 2 Years
Get course recording access for 2 years after course completion.
Aspirational peer group
10K+ students & alumni across diverse domains. Dedicated Telegram virtual classroom for peer-to-peer support.
Instructor
Experts and trainer for top-tech companies.
Direct CRM Calls
Get shortlisted instantly
GitHub Enhancement
Showcase coding skills
Al Mock
Interviews Practice and improve with Al feedback
Placement Assistance Until Placed
Along with up skilling and preparing you for the job, we also help you for your search & your interview.
Mode of Learning
100% Live Learning Learn directly from experienced instructors in Live sessions, with an emphasis on practical, hands-on learning.
Program Name
LinkedIn Optimization
Program Duration
Eligibility
Real time projects
Dedicated Profile Building
Live Doubt Solving
800+ Companies
Certification
LMS Access for 2 Years
Aspirational peer group
Hands-on Industry Relevant Casestudies
Instructor
Direct CRM Calls
GitHub Enhancement
Al Mock Interviews
Mode of Learning
Placement Assistance Until Placed
Syllabus Summary
A Comprehensive Curriculum Designed for Real-World Success
- Type of Statements, Constraints, Clauses
- Functions, Joins, Subqueries, Set Operators
- Analytical Functions, Pivot/Unpivot, Partitions
- Indexes, Views, Sequences, Synonyms
- Performance Tuning
- Stored Procedure & Stored Function
- Cursors, Exception Handling
- Introduction, Data Types (Tuple, List, Dict, Set)
- Control Statements, User-Defined Functions
- String Operations, File & Error Handling
- NumPy, Pandas
- Visualization: Matplotlib, Seaborn
- Automation & Real-World Cases
- Spark Overview
- Spark Architecture
- Transformations, Actions & Lazy Evaluation
- Series & DataFrame Basics
- Spark SQL
- DataFrame Operations
Filtering & Sorting
Built-in Functions & Case Statements
Aggregations & Grouping
Joins & Window Functions
Set Operators
GlobalTemp Views
Analytic Functions
Reading File Formats
Parquet, CSV, JSON
Nested DataFrames - SCD Type 1 (Slowly Changing Dimension)
- SCD Type 2
- Data Factory, Databricks, Synapse
- Storage, Data Lake, Blob Storage, Lake Storage
- Cosmos DB, Logic Apps, API Management
- Event Hub, loT Hub
- Basics & Navigation
- Formulas & Functions
- Data Management
- Charts & Visualization
- Advanced Analysis
- Profile Management with GitHub
Syllabus Summary
A Comprehensive Curriculum Designed for Real-World Success
- Type of Statements, Constraints, Clauses
- Functions, Joins, Subqueries, Set Operators
- Analytical Functions, Pivot/Unpivot, Partitions
- Indexes, Views, Sequences, Synonyms
- Performance Tuning
- Stored Procedure & Stored Function
- Cursors, Exception Handling
- Introduction, Data Types (Tuple, List, Dict, Set)
- Control Statements, User-Defined Functions
- String Operations, File & Error Handling
- NumPy, Pandas
- Visualization: Matplotlib, Seaborn
- Automation & Real-World Cases
- Spark Overview
- Spark Architecture
- Transformations, Actions & Lazy Evaluation
- Series & DataFrame Basics
- Spark SQL
- DataFrame Operations
Filtering & Sorting
Built-in Functions & Case Statements
Aggregations & Grouping
Joins & Window Functions
Set Operators
GlobalTemp Views
Analytic Functions
Reading File Formats
Parquet, CSV, JSON
Nested DataFrames - SCD Type 1 (Slowly Changing Dimension)
- SCD Type 2
- Data Factory, Databricks, Synapse
- Storage, Data Lake, Blob Storage, Lake Storage
- Cosmos DB, Logic Apps, API Management
- Event Hub, loT Hub
- Data visualization using Power BI
- Data Modelling
- Power Query
- Advanced visualizations
- DAX
- Build data analytics project using Power BI
- Basics & Navigation
- Formulas & Functions
- Data Management
- Charts & Visualization
- Advanced Analysis
- Profile Management with GitHub
Top Hiring Industries in India for Data Analytics
Career Support Services
Resume Building
Linkedin Optimaztion
Access To Job Board
Interview Calls
GitHub Portfolio
IntelliBI Azure Data Engineering Certification
Course Highlights
- Course Duration
- 250+ Hours /
- 4 Months
-Pre-Class-
-Pre Career Counseling,
-Technical Evaluation
-Sessions- Technical,
-Softskill, Mentor,
-E-Consultation.
-Technical
-Assignments
-300+ Case Studies
-Industry Real
-World Project 4
-Mock Interviews 5
-Student Internship
-Dashboard
-Resume Preparation,
-Interview Guidance
-Job Readiness,
-Placement support
Our Learners Got Assured Placement. So Can You!
Students reviews
Real stories. Real success.
Real students.
1. Why Learning Azure Data Engineering is a Long-Term Investment:
Cloud computing is the future of business, and its demand will keep growing for the next 100+ years. By 2024, 85% of companies will run their systems on the cloud, powered by increasing amounts of data, AI, IoT, and automation. The global cloud computing market is expected to grow from $600 billion in 2023 to $1.6 trillion by 2030. This growth is creating a high demand for skilled professionals who can manage and optimize cloud infrastructures, especially those with GCP expertise.
Every day, 5 quintillion bytes of data are generated, and businesses need cloud platforms like Azure to store, process, and analyze this massive data. As data continues to grow, cloud platforms will become essential for handling large-scale data operations.
Companies are now offering lower salaries for those without expertise in cloud technologies. Many companies and clients are urging professionals to get certified in cloud platforms like Azure, recognizing the increasing importance of these skills. This is the perfect time to adopt cloud technologies and gain certifications, as it opens doors to high-paying job opportunities.
By learning Azure Data Engineering, you can not only advance your career but also position yourself for a stable, rewarding future in the ever-expanding cloud industry.
2. Pre-requisites:
- SQL & PL/SQL (Stored Functions, Stored Procedures, Indexes)
- Python
- Spark (PySpark, Spark SQL)
3. Azure Services: A Must for Data Engineers:
- Azure Data Factory
- Azure Databricks
- Azure Synapse
- Azure Storage
- Azure Data Lake
- Azure Blob Storage
- Azure Data Lake Storage
- Azure Cosmos DB
- Azure Logic Apps
- Azure Machine Learning
- Azure API Management
- Azure Event Hub
- Azure IoT Hub
4. Comparing Coding Complexity: Azure Data Engineers vs Java Developers
Azure Data Engineers: Coding complexity is around 50% compared to Java Developers, where the complexity is considered 100%.
5. Career Opportunities:
- For Experienced Professionals:
- Azure Data Engineer
- Cloud Data Engineer
- Big Data Engineer
- Data Analyst
- Business Intelligence Developer
- Cloud Solutions Architect
- For Freshers:
- Azure Data Engineer
- Cloud Data Engineer
- Data Analyst
- SQL Developer
- Python Developer
- Big Data Engineer
6. Job Opening:
The demand for Azure Data Engineering roles is growing rapidly and contributes to about 55-60% of the job market in the cloud and data fields.
7. Eligibility Criteria:
Educational Background: Minimum Requirement: A bachelor’s degree must be completed.
- Eligible Degrees:
- BE (all streams)
- B.Tech
- BCS
- BCA
- B.Com
- BBA
- Other related technical or non-technical bachelor’s fields
- And its relevant postgraduate degrees
- Diploma Holders:
- All streams may also be eligible.
- Communication Skills:
- Basic written and verbal communication skills.
- Ability to explain technical concepts clearly.
8. The Future of Data Engineering with Azure:
Demand & Growth: The demand for Azure Data Engineers is expanding across sectors like finance, healthcare, e-commerce, and manufacturing. Reports show that the global cloud computing market is expected to grow from $600 billion in 2023 to $1,600 billion by 2030, driving an increase in demand for Azure professionals.
Job Growth: According to the US Bureau of Labor Statistics, employment in cloud computing roles is projected to grow by 22% from 2020 to 2030, much faster than the average for all occupations. Similarly, job boards like LinkedIn and Indeed show an increasing number of job postings specifically targeting Azure Data Engineers as companies continue to scale their data infrastructure.
Increasing Data Roles: As businesses rely more on data, the role of Azure Data Engineers becomes more essential. By 2030, over 85 million jobs will require advanced data skills, strengthening the job security for Azure Data Engineers.
9. Annual CTC for Azure Data Engineers (Based on Experience):
- 0-1 Year Experience (Entry-Level):
- India: ₹4–6 LPA
- US: $60,000–$80,000
Job Role: Support data tasks, learn cloud tech, assist with data pipelines and cloud infrastructure setup
- 1-4 Years Experience (Junior/Mid-Level):
- India: ₹6–14 LPA
- US: $80,000–$110,000
Job Role: Build and manage data pipelines, handle data integration, optimize cloud environments, and automate processes.
- 4-8 Years Experience (Mid-Level/Senior):
- India: ₹10–25 LPA
- US: $110,000–$140,000
Job Role: Lead data architecture, develop ETL pipelines, mentor junior engineers, and handle large-scale data projects.
- 8+ Years Experience (Senior/Lead):
- India: ₹20–55+ LPA
- US: $140,000–$160,000+
Job Role: Oversee cloud data solutions, manage teams, lead strategic data projects, ensure system scalability, and optimize data flow.
Summary:
Azure Data Engineering offers significant salary growth with experience, ranging from ₹4-6 LPA (India) and $60,000–$80,000 (US) for entry-level roles to ₹20–55+ LPA (India) and $140,000–$160,000+ (US) for senior roles.
Pre-requisites:
- SQL & PL/SQL (Stored Functions, Stored Procedures, Indexes)
- Python
- Spark (PySpark, Spark SQL)
Azure Services: A Must for Data Engineers:
- Azure Data Factory
- Azure Databricks
- Azure Synapse
- Azure Storage
- Azure Data Lake
- Azure Blob Storage
- Azure Data Lake Storage
- Azure Cosmos DB
- Azure Logic Apps
- Azure Machine Learning
- Azure API Management
- Azure Event Hub
- Azure IoT Hub