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Azure data engineering is a rapidly growing field with tremendous potential for career growth and advancement. Here are some reasons why you might want to consider a career as an Azure data engineer


High Demand

With the increasing amount of data generated in today's digital world, companies are in need of data engineers to help them manage and analyze this data. According to LinkedIn, data engineer is one of the top emerging jobs in the US, and demand for data engineers is projected to grow at a faster rate than other IT jobs.

Lucrative Salary

Data engineering is a highly specialized skill, and as such, it can command a high salary. According to Glassdoor, the average salary for a data engineer in the US is over $115,000 per year.

Variety of Work

As an Azure data engineer, you will have a range of responsibilities, from designing and building data pipelines to creating data models and visualizations. This variety can make the work more interesting and engaging.

Continuous Learning

Technology is constantly evolving, and as a data engineer, you will need to stay up-to-date with the latest tools and techniques. This can provide an ongoing challenge and opportunities for personal and professional growth.


Many data engineering jobs offer remote work options, allowing you to work from home or anywhere in the world with an internet connection.

Azure data engineering is a dynamic and rewarding career path
that offers excellent career prospects and opportunities for growth.

Roadmap for becoming an Azure Data Engineer in 2023


Why Azure Data Engineer Certification Course from Coding Superstar?

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Quizzes and assignments

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10 weeks

Time Duration

Real-time Projects


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DP203 Exam Clearing


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Tools Covered

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How Azure data engineer certification course will benefit you?

Azure certification course facilitates long-term career advancement, salary growth, and the increase of job opportunities. According to a recent survey, 93% of decision-makers concur that qualified employees add value to themselves. Their right choice to enroll in the Azure data engineering certification course has a direct impact on the pay scale and better job opportunities.

Azure Data Engineer Certification Curriculum

Curriculum Designed by Experts

Design and Implement Data Storage

Download Syllabus
Design a data storage structure
Design an Azure Data Lake solution
Recommend file types for storage
Recommend file types for analytical queries
Design for efficient querying
Design for data pruning
Design a folder structure that represents the levels of data transformation
Design a distribution strategy
Design a data archiving solution
Design a partition strategy
Design a partition strategy for files
Design a partition strategy for analytical workloads
Design a partition strategy for efficiency/performance
Design a partition strategy for Azure Synapse Analytics
Identify when partitioning is needed in Azure Data Lake Storage Gen2
Design the serving layer
Design star schemas
Design slowly changing dimensions
Design a dimensional hierarchy
Design a solution for temporal data
Design for incremental loading
Design analytical stores
Design metastores in Azure Synapse Analytics and Azure Databricks
Implement physical data storage structures
Implement compression
Implement partitioning
Implement sharding
Implement different table geometries with Azure Synapse Analytics pools
Implement data redundancy
Implement distributions
Implement data archiving
Implement logical data structures
Build a temporal data solution
Build a slowly changing dimension
Build a logical folder structure
Build external tables
Implement file and folder structures for efficient querying and data pruning
Implement logical data structures
Deliver data in a relational star schema
Deliver data in Parquet files
Maintain metadata
Implement a dimensional hierarchy

Design and Develop Data Processing

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Ingest and transform data
Transform data by using Apache Spark
Transform data by using Transact-SQL
Transform data by using Data Factory
Transform data by using Azure Synapse Pipelines
Transform data by using Stream Analytics
Cleanse data
Split data
Shred JSON
Encode and decode data
Configure error handling for the transformation
Normalize and denormalize values
Transform data by using Scala
Perform data exploratory analysis
Design and develop a batch processing solution
Develop batch processing solutions by using Data Factory, Data Lake, Spark, Azure Synapse Pipelines, PolyBase, and Azure Databricks
Create data pipelines
Design and implement incremental data loads
Design and develop slowly changing dimensions
Handle security and compliance requirements
Scale resources
Configure the batch size
Design and create tests for data pipelines
Integrate Jupyter/IPython notebooks into a data pipeline
Handle duplicate data
Handle missing data
Handle late-arriving data
Upsert data
Regress to a previous state
Design and configure exception handling
Configure batch retention
Design a batch processing solution
Debug Spark jobs by using the Spark UI
Design and develop a stream processing solution
Develop a stream processing solution by using Stream Analytics, Azur Databricks, and Azure Event Hubs
Process data by using Spark structured streaming
Monitor for performance and functional regressions
Design and create windowed aggregates
Handle schema drift
Process time series data
Process across partitions
Configure checkpoints/watermarking during processing
Scale resources
Design and create tests for data pipelines
Optimize pipelines for analytical or transactional purposes
Handle interruptions
Design and configure exception handling
Upsert data
Replay archived stream data
Design a stream processing solution
Manage batches and pipelines
Trigger batches
Handle failed batch loads
Validate batch loads
Manage data pipelines in Data Factory/Synapse Pipelines
Schedule data pipelines in Data Factory/Synapse Pipelines
Implement version control for pipeline artifacts
Manage Spark jobs in a pipeline

Design and Implement Data Security

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Design security for data policies and standards
Design data encryption for data at rest and in transit
Design a data auditing strategy
Design a data masking strategy
Design for data privacy
Design a data retention policy
Design to purge data based on business requirements
Design Azure role-based access control (Azure RBAC) and POSIX-like Access
Control List (ACL) for Data Lake Storage Gen2
Design row-level and column-level security
Implement data security
Implement data masking
Encrypt data at rest and in motion
Implement row-level and column-level security
Implement Azure RBAC
Implement POSIX-like ACLs for Data Lake Storage Gen2
Implement a data retention policy
Implement a data auditing strategy
Manage identities, keys, and secrets across different data platform technologies
Implement secure endpoints (private and public)
Implement resource tokens in Azure Databricks
Load a DataFrame with sensitive information
Write encrypted data to tables or Parquet files
Manage sensitive information

Monitor and Optimize Data Storage and Data Processing

Download Syllabus
Monitor data storage and data processing
Implement logging used by Azure Monitor
Configure monitoring services
Measure performance of data movement
Monitor and update statistics about data across a system
Monitor data pipeline performance
Measure query performance
Monitor cluster performance
Understand custom logging options
Schedule and monitor pipeline tests
Interpret Azure Monitor metrics and logs
Interpret a Spark directed acyclic graph (DAG)
Optimize and troubleshoot data storage and data processing
Compact small files
Rewrite user-defined functions (UDFs)
Handle skew in data
Handle data spill
Tune shuffle partitions
Find shuffling in a pipeline
Optimize resource management
Tune queries by using indexers
Tune queries by using cache
Optimize pipelines for analytical or transactional purposes
Optimize pipeline for descriptive versus analytical workloads
Troubleshoot a failed spark job
Troubleshoot a failed pipeline run

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  Download Syllabus

First 3 Days Classes From One Of Previous Batches


Azure Data Engineer Class 1


Azure Data Engineer Class 2


Azure Data Engineer Class 3


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Success Stories

“ Azure Data Engineer Training at Coding Superstar is pure value for your learning investment. Trainer Karthik is very knowledgeable and has great insight on the subject. Two major projects were covered which immensely increase the weightage of my resume. Highly recommended for anybody building career In Azure Data Engineer. ”

“ After taking 12 demos from different trainers on Azure Data Engineer, trainer Karthik’s presentation we liked the most for his deep knowledge and easy way of expalnation.Guys if any of you readng this want to opt for Azure Data Engineer training, ask their team for free demo session. You will definitely like it as I did. All the best to all and Thank you team Coding Superstar! ”

“ Microsoft Azure training at coding superstar was very helpful. I took azure admin and solution architect combo course. The mentor was very knowledgeable. Strongly recommended.. ”

“ Excellent and knowledgeable trainer. I recommend this institute to learn Azure. Completed as per my exact requirement with lightening speed. ”

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Learn the data skills you need online at your own pace—from non-coding essentials to data science and machine learning.

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Azure Data Engineer FAQs

What is Azure data engineer?
A certified Azure Data Engineer is responsible for combining, transforming, and integrating data from innumerable data sources into a structure. The complete architecture of data flows is shaped by Azure Data Engineer.
What is Azure data engineer certification?
In Azure Data Engineer certification, the candidate is tested for his knowledge of building and maintaining compliant and secure data processing pipelines through various tools and methods.
What certification for azure data engineer is available?
The only certification available for azure data engineering is “Exam DP-203: Microsoft Azure for data engineering.
Who should take part in this certification course?
To obtain certification as an Azure Data Engineer, an aspirant has to follow these steps:

● Enroll in Azure data engineering training to master this IT field
● The aspirant will gain a comprehensive understanding by working on real-world projects and use cases.
● Clear the test and get certified.

How can an aspirant get azure data engineer certification?
Business intelligence professionals, ETL developers, data analysts, and fresh graduates can be benefitted from this Azure Data Engineering certification course.
How can an aspirant get azure data engineer certification?
The best quality training for freshers and professionals is available at Coding Superstar. It covers everything that an aspirant needs to know to become a certified Azure Data Engineer. You can pass the Azure Data Engineer certification with the help of Coding Superstar’s live instructor-led training, self-paced videos, assignments, up-to-date course materials, learning management system (LMS), recordings of training sessions, 24/7 live support, and certification guidance.
Does Coding Superstar offer placements once done with the training?
Yes, Coding Superstar helps all students with placement via mock interviews, the creation of your resume, and the forwarding of your profile to our corporate clients who are looking for trained candidates.
Which jobs certified Azure data engineers will get?
Aspirants can become Azure Data Engineer, Data Engineer, ETL Developer, or Azure Data Factory Developer once completed azure data engineer training and pass tests and obtain certification.