Serving Preet Vihar, Delhi ISO 9001:2015 Recognized 100% Placement Support

Data Engineering Big Data & Data Pipeline Course in Preet Vihar, Delhi

Advance your professional career with the Data Engineering Big Data & Data Pipeline Course at SSSAM Academy. Specially tailored for students and working professionals from Preet Vihar (Delhi), featuring hands-on live projects, industry-standard toolchains, and 100% placement support.

Physical Classroom Campus SSSAM Academy, M24 Ground Floor, Old DLF Colony, Sector 14, Gurugram
Delivery Mode for Preet Vihar (Delhi) Live interactive online batches with recorded portal access, plus full access to our Sector 14 Gurugram physical lab (Approx. 39 km (typically 70-80 mins via NH-48) or Blue-to-Yellow Metro route).
Explore Syllabus ↓
Industry Veteran Mentors Live Real-Time Projects Weekday & Weekend Batches Classroom Labs + Live Online

Duration

3 Months (Fast-Track Available)

Learning Mode

Classroom & Live Interactive Online

Certification

Govt. Recognized & ISO 9001:2015

Placement

100% Dedicated Placement Assistance

About the Data Engineering Big Data & Data Pipeline Course Program for Preet Vihar Learners

Conveniently accessible via Approx. 39 km (typically 70-80 mins via NH-48) or Blue-to-Yellow Metro route, students and professionals in Preet Vihar (Delhi) near Preet Vihar Metro, Metro Pillar 110, and Vikas Marg commercial stretch can easily master SSSAM Academy’s premier Data Engineering Big Data & Data Pipeline Course. Specifically designed for East Delhi students from surrounding CBSE schools, colleges, and finance/accounting trainees, this course combines practical classroom lab accelerators at our Sector 14 Gurugram facility with interactive online cohorts to ensure every learner builds a job-ready portfolio.

Local Community & Career Scope: Preet Vihar is one of Delhi prominent east delhi commercial areas, hosting thousands of college graduates, competitive aspirants, and software engineers seeking high-paying IT placements across Delhi NCR.

Commute & Learning Options: Accessible in 25-50 minutes via Preet Vihar Metro (Blue Line) directly connecting to the Yellow Line (Guru Dronacharya / MG Road) or via NH-48 Expressway. For students preferring remote study, SSSAM Academy provides live interactive online batches with recorded sessions, digital notes, and full placement support.

Data Engineering Big Data & Data Pipeline Course Detailed Curriculum & Modules

Structured step-by-step from core fundamentals to real-world industrial capstone projects.

Main Topic 1: Big Data Architecture & PySpark — RDDs, DataFrames, Spark SQL, Spark Submit, Distributed Computing Main Topic 2: Columnar Data Storage Formats — Parquet vs ORC vs Avro, Compression (Snappy/Gzip), Partitioning Strategies Practical Capstone: Building a Distributed Data Ingestion Engine with PySpark

Main Topic 1: Dimensional Data Modeling — Star Schema vs Snowflake Schema, Fact Tables, Dimension Tables, SCD Type 1 & 2 Main Topic 2: Cloud Data Warehouses — Snowflake Virtual Warehouses, AWS Redshift Spectrum, COPY Commands, Staging Practical Capstone: Designing an Enterprise Cloud Data Warehouse in Snowflake

Main Topic 1: Apache Airflow DAGs — Workflow Orchestration, Operators, Tasks, Scheduling, XComs, Backfilling Main Topic 2: Real-Time Streaming with Apache Kafka — Producers, Consumers, Topics, Kafka Connect, Streaming Analytics Practical Capstone: End-to-End Real-Time ETL Pipeline Orchestrated via Apache Airflow & Kafka

Database schema design Indexing and performance optimization Data normalization and integrity Working with large datasets in databases

ETL concepts (Extract, Transform, Load) Building automated data pipelines Data transformation techniques Data warehousing fundamentals

Star and snowflake schema design Batch and streaming data processing Introduction to big data processing frameworks Data pipeline monitoring and maintenance

Why Choose SSSAM Academy in Delhi?

Industry Veteran Mentors

Learn directly from senior software developers and subject matter experts with 8+ years of real corporate project experience.

Live Real-Time Projects

Build portfolio-grade live projects and case studies that make your resume stand out in top corporate interviews.

100% Placement Support

Dedicated placement wing assisting you with resume crafting, LinkedIn optimization, mock interviews, and recruitment drives.

Top Hiring in Delhi & NCR

Target direct interviews with hiring companies across Preet Vihar and NCR: Top recruitment hubs across Connaught Place, Nehru Place, Gurgaon Cyber City, and South Delhi tech startups including Paytm, Zomato, TCS, and Infosys.

Ready to Master Data Engineering Big Data & Data Pipeline Course in Preet Vihar?

Join hundreds of successful alumni working at top tech firms across India. Reserve your seat for the upcoming batch with special discounts & free career counseling.

Chat on WhatsApp

Frequently Asked Questions (FAQs)

What are the eligibility requirements for the Data Engineering Course?

Familiarity with SQL databases and basic Python programming is recommended. Tailored for software developers, database administrators, and data analysts advancing into big data engineering.

What practical projects will I build during the Data Engineering Course?

You will build scalable big data pipelines: streaming real-time IoT events via Apache Kafka, batch processing datasets with Apache Spark (PySpark), storing in a Cloud Data Lake, and orchestrating DAG workflows in Apache Airflow.

What career support and job roles are available after completing Data Engineering Course?

Qualifies you for high-demand positions like Big Data Engineer, Data Pipeline Associate, and ETL Developer, commanding entry-level salaries competitive entry-level compensation aligned with Delhi NCR industry benchmarks.

How can students from Preet Vihar, Delhi attend Data Engineering Big Data & Data Pipeline Course classes?

Learners from Preet Vihar can balance their college or office schedules by choosing our live interactive online batches during weekdays and attending weekend intensive project labs in Sector 14.