Master the Fundamental Concepts of Data Engineer. Enroll today and become a skilled Data Engineer expert.
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40 Hrs.Live Project
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Speciality
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Professionals Trained
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Countries & Counting
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Corporate Served- The Data Engineer Course in Delhi is designed for individuals who wish to develop the skills needed to work with large datasets, build data pipelines, and ensure data systems are scalable, efficient, and reliable. This course covers fundamental topics like data warehousing, ETL (Extract, Transform, Load) processes, big data technologies, cloud computing, and programming languages like Python, SQL, and Spark. Data Engineer Training in Delhi prepares students for real-world data engineering challenges, making them industry-ready for top data roles.
Data Engineer Course in Delhi
- The Data Engineer Course in Delhi aims to equip students with the technical knowledge required for data management and engineering roles. By the end of Data Engineer Classes in Delhi, students will be proficient in building data systems, managing databases, and handling large-scale data processing.
Learn the basics of data engineering and how data flows within an organization.
Master key technologies like SQL, Hadoop, Spark, and cloud platforms (AWS, Azure).
Understand ETL processes, data warehousing, and data pipeline architecture.
Gain hands-on experience with real-time data processing and management.
Explore techniques for optimizing data storage, processing, and retrieval.
- Freshers who complete the Data Engineering Classes in Delhi can expect competitive salaries due to the high demand for skilled professionals in this field. Depending on the organization and skill level, the salary for a fresher typically ranges from 4.5 LPA to 7 LPA.
Entry-level data engineers: 4.5 - 7 LPA.
The salary may increase significantly with experience and expertise.
Professionals can earn higher salaries with proficiency in big data tools and cloud technologies.
- After completing the Data Engineer Course in Delhi, students can advance their careers in several directions. As a data engineer, you will have a clear career path with potential promotions to senior data engineer roles, data architect positions, or even managerial roles in data teams.
Junior Data Engineer Senior Data Engineer Data Architect.
With expertise, you can take leadership roles like Data Engineering Manager or Director of Data Engineering.
Continuous learning and certifications will lead to better job opportunities and higher salaries.
- The Data Engineering Training in Delhi is popular due to the growing demand for data professionals in various industries. Data engineering is the backbone of data analytics and machine learning, and as businesses collect more data, the need for qualified data engineers is increasing.
Data engineering is a high-demand, future-proof career.
The course provides in-depth knowledge of industry-leading tools and technologies.
Delhi is a tech hub with numerous job opportunities for data engineers.
The course offers hands-on training with real-world projects.
- Once you complete the Data Engineer Course in Delhi, youll be prepared to take on various job roles in the data field. Your role will revolve around building and maintaining robust data infrastructure, ensuring smooth data operations, and providing clean and usable data for analysis.
Building and maintaining data pipelines.
Managing databases and cloud infrastructure.
Ensuring data quality and availability for analytics teams.
Collaborating with data scientists to ensure effective data use.
Optimizing data storage and processing systems.
- Industries in Delhi and across India are constantly looking for skilled data engineers. The following sectors are particularly in need of data engineers:
Information Technology (IT): Companies developing software solutions.
Finance & Banking: To analyze and manage large amounts of transactional data.
E-commerce: Handling user data for analytics and business insights.
Healthcare: Managing patient data for research and decision-making.
Telecommunications: Analyzing data from customer networks and services.
- Upon completion of the Data Engineer Course in Delhi, students will receive a certificate that validates their skills and expertise in data engineering. This certificate enhances job prospects and serves as a proof of knowledge for potential employers.
- Our placement process is designed to connect students with top companies in the industry. We provide placement assistance, including interview preparation, resume building, and mock interviews to ensure students are ready for their job search.
Resume-building workshops and interview preparation sessions.
Collaboration with top tech companies for placements.
Dedicated placement cell to guide students through job applications.
Why Should You Choose Data Engineering Course?
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Course Duration
40 Hrs.
Flexible Batches For You
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30-Apr-2025*
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03-May-2025*
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05-May-2025*
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30-Apr-2025*
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CURRICULUM & PROJECTS
Data Engineering Certification Course
- Understand the purpose of data modeling.
- Identify the strengths and weaknesses of different types of databases and data storage techniques.
- Create a table in Apache Cassandra.
- Understand when to use a relational database.
- Understand the difference between OLAP and OLTP databases.
- Create normalized data tables.
- Implement denormalized schemas (e.g. STAR, Snowflake).
- Understand when to use NoSQL databases and how they differ from relational databases.
- Select the appropriate primary key and clustering columns for a given use case.
- Create a NoSQL database in Apache Cassandra.
- Explain how OLAP may support certain business users better than OLTP.
- Implement ETL for OLAP Transformations with SQL.
- Describe Data Warehouse Architecture.
- Describe OLAP cube from facts and dimensions to slice, dice, roll-up, and drill down operations.
- Implement OLAP cubes from facts and dimensions to slice, dice, roll-up, and drill down.
- Compare columnar vs. row-oriented approaches.
- Implement columnar vs. row-oriented approaches.
- Explain the differences between ETL and ELT.
- Differentiate scenarios where ELT is preferred over ETL.
- Implement ETL for OLAP Transformations with SQL.
- Select appropriate cloud data storage solutions.
- Select appropriate cloud pipeline solutions.
- Select appropriate cloud data warehouse solutions.
- Describe AWS data warehouse services and technologies.
- Create and configure AWS Storage Resources.
- Create and configure Amazon Redshift resources.
- Implement infrastructure as code for Redshift on AWS.
- Describe Redshift data warehouse architecture.
- Run ETL process to extract data from AWS S3 into Redshift.
- Design optimized tables by selecting appropriate distribution styles and sorting keys.
- Identify what constitutes the big data ecosystem for data engineering.
- Explain the purpose and evolution of data lakes in the big data ecosystem.
- Compare the Spark framework with Hadoop framework.
- Identify when to use Spark and when not to use it.
- Describe the features of lakehouse architecture.
- Wrangle data with Spark and functional programming to scale across distributed systems.
- Process data with Spark DataFrames and Spark SQL.
- Process data in common formats such as CSV and JSON.
- Use the Spark RDDs API to wrangle data.
- Transform and filter data with Spark.
- Use distributed data storage with Amazon S3.
- Identify properties of AWS S3 data lakes.
- Identify service options for using Spark in AWS.
- Configure AWS Glue.
- Create and run Spark Jobs with AWS Glue.
- Use Spark with AWS Glue to run ELT processes on data of diverse sources, structures, and vintages in lakehouse architecture.
- Create a Glue Data Catalog and Glue Tables.
- Use AWS Athena for ad-hoc queries in a lakehouse.
- Leverage Glue for SQL AWS S3 queries and ELT.
- Ingest data into lakehouse zones.
- Transform and filter data into curated lakehouse zones with Spark and AWS Glue.
- Join and process data into lakehouse zones with Spark and AWS Glue.
- Define and describe a data pipeline and its usage.
- Explain the relationship between DAGs, S3, and Redshift within a given example.
- Employ tasks as instantiated operators.
- Organize task dependencies based on logic flow.
- Apply templating in codebase with kwargs parameter to set runtime variables.
- Create Airflow Connection to AWS using AWS credentials.
- Create Postgres/Redshift Airflow Connections.
- Leverage hooks to use Connections in DAGs.
- Connect S3 to a Redshift DAG programmatically.
- Utilize the logic flow of task dependencies to investigate potential errors within data lineage.
- Leverage Airflow catchup to backfill data.
- Extract data from a specific time range by employing the kwargs parameters.
- Create a task to ensure data quality within select tables.
- Consolidate repeated code into operator plugins.
- Refactor a complex task into multiple tasks with separate SQL statements.
- Convert an Airflow 1 DAG into an Airflow 2 DAG.
- Construct a DAG and custom operator end-to-end.
Mock Interviews
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FAQ's
Basic knowledge of programming languages like Python and SQL is recommended.
With hands-on training and certifications, students have a high chance of securing a job shortly after completing the course.
The duration of the course typically ranges from 3 to 6 months, depending on the program.
Yes, Data Engineering Course in Delhi includes comprehensive training in cloud platforms (AWS, Azure) and big data technologies like Hadoop and Spark.
Some institutes may offer a satisfaction guarantee or refund policy. It’s best to confirm this with the Data Engineer Training in Delhi provider.
- - Build an Impressive Resume
- - Get Tips from Trainer to Clear Interviews
- - Attend Mock-Up Interviews with Experts
- - Get Interviews & Get Hired
If yes, Register today and get impeccable Learning Solutions!
Training Features
Instructor-led Sessions
The most traditional way to learn with increased visibility,monitoring and control over learners with ease to learn at any time from internet-connected devices.
Real-life Case Studies
Case studies based on top industry frameworks help you to relate your learning with real-time based industry solutions.
Assignment
Adding the scope of improvement and fostering the analytical abilities and skills through the perfect piece of academic work.
Lifetime Access
Get Unlimited access of the course throughout the life providing the freedom to learn at your own pace.
24 x 7 Expert Support
With no limits to learn and in-depth vision from all-time available support to resolve all your queries related to the course.
Certification
Each certification associated with the program is affiliated with the top universities providing edge to gain epitome in the course.
Showcase your Course Completion Certificate to Recruiters
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