Azure Data Engineering Course in Hyderabad
Build cloud data pipelines and lakehouses on Azure end to end
The Azure Data Engineering course teaches you to design and build data platforms on Microsoft Azure. You start with SQL, Python and data modelling, then work through Azure Data Lake Storage Gen2, Azure Data Factory for orchestration and ingestion, Azure Databricks and Apache Spark for large-scale transformation, Delta Lake and the medallion architecture, Azure Synapse Analytics and Azure SQL for serving data, and Azure Event Hubs with Stream Analytics for streaming. You also cover security with Microsoft Entra ID and Key Vault, governance with Microsoft Purview, CI/CD with Azure DevOps, monitoring and cost control. Microsoft retired the DP-203 Azure Data Engineer Associate exam and now certifies data engineers on Microsoft Fabric (DP-700), so the course includes a module on how the same concepts map to Fabric, and a counsellor will confirm current certification options. It suits graduates and professionals with basic SQL who want data engineer roles; Python is taught from the basics. You finish with a capstone pipeline that ingests, transforms, serves and monitors data. Classes run in Ameerpet, Hyderabad, and online.
Syllabus
Data Engineering Foundations
- •Roles and responsibilities of a data engineer
- •Data warehouse, data lake and lakehouse architectures
- •Batch versus streaming; ETL versus ELT
- •Lab: Map the architecture of a sample analytics platform
- •Outcome: Describe how a modern data platform fits together
SQL & Python for Data Engineers
- •SQL: joins, aggregations, CTEs and window functions
- •Python basics, functions and pandas for data wrangling
- •File formats: CSV, JSON, Parquet, Avro
- •Lab: Clean and transform a sample dataset with SQL and Python
- •Outcome: Write the SQL and Python used in pipeline logic
Azure Fundamentals for Data Platforms
- •Azure resource hierarchy, regions and pricing basics
- •Microsoft Entra ID, RBAC and managed identities
- •Networking basics: private endpoints and firewalls
- •Lab: Create a secure resource group for a data project
- •Outcome: Provision secure Azure resources for data work
Azure Data Lake Storage Gen2
- •Storage accounts with hierarchical namespace
- •Folder design for raw, curated and serving zones
- •RBAC and ACLs, lifecycle management and cost tiers
- •Lab: Build a lake structure and load sample files
- •Outcome: Organise and secure a data lake
Azure Data Factory Pipelines
- •Linked services, datasets, pipelines and activities
- •Copy activity, parameters, expressions and metadata-driven design
- •Triggers, integration runtimes and error handling
- •Mapping data flows for transformation
- •Lab: Build an incremental load from SQL to the lake
- •Outcome: Orchestrate reliable ingestion pipelines
Azure Databricks & Apache Spark
- •Databricks workspace, clusters and notebooks
- •PySpark DataFrames, Spark SQL and joins at scale
- •Performance basics: partitioning, caching and shuffles
- •Lab: Transform a multi-million-row dataset with PySpark
- •Outcome: Process large datasets with Spark
Delta Lake & Medallion Architecture
- •Delta Lake tables, ACID transactions and schema enforcement
- •MERGE, time travel, optimise and vacuum
- •Bronze, silver and gold layers
- •Lab: Build a three-layer lakehouse with incremental merge
- •Outcome: Build reliable, query-ready lakehouse tables
Azure Synapse Analytics & Serving Layer
- •Dimensional modelling: facts, dimensions and star schema
- •Synapse serverless and dedicated SQL pools overview; Azure SQL Database
- •Loading and querying curated data; connecting Power BI
- •Lab: Publish a gold layer and build a simple report
- •Outcome: Serve analytics-ready data to reporting tools
Streaming with Event Hubs & Stream Analytics
- •Event-driven architecture and Azure Event Hubs
- •Azure Stream Analytics queries and windowing
- •Structured Streaming in Databricks
- •Lab: Process a stream of events into the lake
- •Outcome: Build near real-time ingestion
Security, Governance & Quality
- •Azure Key Vault, managed identities and secure linked services
- •Microsoft Purview for catalogue, lineage and classification
- •Data masking, row-level security and data quality checks
- •Lab: Remove secrets from pipelines and register assets in Purview
- •Outcome: Make pipelines secure and auditable
DevOps, Monitoring & Cost Control
- •Git integration for Data Factory and Databricks Repos
- •CI/CD with Azure DevOps pipelines across environments
- •Azure Monitor, pipeline alerts and failure handling
- •Cost management and workload optimisation
- •Lab: Promote a pipeline from dev to test with a release pipeline
- •Outcome: Operate data pipelines in production
Microsoft Fabric Bridge
- •How Fabric relates to Synapse, Data Factory and Power BI
- •OneLake, lakehouse and Fabric data pipelines overview
- •Mapping Azure data engineering skills to current Fabric certification
- •Lab: Recreate a small pipeline in a Fabric trial workspace
- •Outcome: Transfer skills between Azure services and Fabric
Capstone & Interview Preparation
- •Capstone: batch and streaming pipeline with lakehouse, serving layer and monitoring
- •Architecture documentation and GitHub portfolio
- •SQL, Spark and design interview practice
- •Outcome: A portfolio-ready data platform project
Tools Covered
Projects Included
- Retail Sales Lakehouse: Ingest sales data into ADLS Gen2, transform with Databricks and publish gold tables; deliverable is a three-layer Delta pipeline and data dictionary.
- Metadata-Driven Ingestion Framework: Build a parameterised Data Factory pipeline that loads many source tables incrementally; deliverable is a reusable pipeline and runbook.
- Streaming Telemetry Pipeline: Process events from Event Hubs into the lake and a reporting table; deliverable is a working stream with windowed aggregates.
- Governed Analytics Mart: Model a star schema in Synapse or Azure SQL with Purview classifications; deliverable is a documented model and Power BI report.
- Capstone Data Platform: Combine batch, streaming, CI/CD and monitoring into one project with cost notes; deliverable is a GitHub repository and architecture diagram.
Start Your Journey Today
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Call: +91 9908099980Prerequisites & Eligibility
Understand the foundation and skills needed to succeed in the Azure Data Engineering course.
Course Prerequisites
- Any graduate is eligible for enrollment across all program tracks
- Dedication to work on real-time scenario projects and live client project implementations
- Willingness to engage in aptitude, soft skills and interview readiness sessions
- Commitment to complete full-day training or intensive/internship program schedules
Why Choose GloryTecks
Build practical capabilities through structured learning, expert mentors and hands-on projects.
5+ Years of Excellence
Established training institute in Hyderabad with a proven track record of producing industry-ready professionals.
Expert Faculty
Learn from trainers with real-world industry experience, who teach the way the work is actually done.
Placement Assistance
A dedicated placement team with tie-ups across hiring companies. We support you until you get hired.
Comprehensive Curriculum
Updated syllabus covering the latest technologies and industry best practices, with hands-on projects.
Career Growth Focus
Not just training, but complete career transformation with soft skills and interview preparation.
Online & Classroom
Attend live online batches or classroom training at our Ameerpet centre, whichever suits you.
Flexible Batches
Weekday, weekend and online batch timings to suit working professionals, students and freshers.
Real-time Projects
Work on real-time scenario projects so you finish with practical experience to show employers.
We provide placement support with direct access to hiring companies, along with comprehensive training that helps freshers become job-ready professionals.
Certification
Explore certification and practical learning opportunities with a focus on Azure Data Engineering.
Certificate of Completion
Azure Data Engineering
This certifies that
[Your Name]
has successfully completed the
Azure Data Engineering
Training Program
GloryTecks
Ameerpet, Hyderabad
Certificate ID
GT-YYYY-XXXX
Certificate Includes
- Course completion certificate from GloryTecks
- Project completion certificates
- Internship completion certificate for eligible internship programs
- Digital certificate with a unique verification ID
- Shareable on LinkedIn and other professional platforms
- Valid proof of skill acquisition for employers
- Includes the detailed syllabus covered
Industry Focus
A certificate built around the tools and skills employers ask for, adding credibility to your resume.
Skill Validation
Proves your expertise in the course and the technologies you worked with.
Career Advancement
Strengthens your profile when you apply for jobs and negotiate your salary.
Digital & Physical
Get a digital certificate for online sharing and a physical copy for framing.
Course Certificate
Upon successful completion of the training program
Project Certificate
For major projects completed during training
Course Features & Highlights
Build a strong foundation through a structured Azure Data Engineering course with practical learning and hands-on exposure.
Live Projects
Work on real-world projects from day one with industry use cases.
Expert Trainers
Learn from industry professionals with real-world experience.
Placement Support
Dedicated placement team with assistance until you get hired.
Industry Certification
Get certified and boost your resume with recognized credentials.
LMS Access
Access to learning materials and recorded sessions.
Mock Interviews
Weekly mock interviews to prepare you for real job scenarios.
Resume Building
Professional resume preparation and LinkedIn profile optimization.
Additional Benefits
- Flexible Payment Plans
- 6-12 Months LMS Access
- Doubt Clearing Sessions
- 24/7 Learning Support
Frequently asked questions
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Best Azure Data Engineering Training in
Ameerpet, Hyderabad
Located at Ameerpet — Hyderabad’s IT training hub. Easily accessible from all areas of Hyderabad. Just 2 minutes walk from Ameerpet Metro Station.
Placement Support
Career support covers resume and LinkedIn preparation, mock interviews and a portfolio of 5 course projects. Roles that use these skills include Azure Data Engineer, Data Engineer, ETL Developer, Big Data Developer; support is guidance with the job search, not a guarantee of a job.