Best Data Engineering with AI in
Varanasi
Accelerate your engineering career with 100% placement assurance, high-tech offline laboratory training, 100+ Hours+ hours of intensive live projects, and 1-on-1 mentorship from top architects.
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4Achievers Varanasi Tech Campus
Experience focused, mentor-led offline learning equipped with state-of-the-art workstations, high-speed internet, dedicated faculty doubt counters, and air-conditioned classrooms.
Data Engineering with AI Syllabus in Varanasi
Curriculum co-designed with engineering leads from tier-1 MNCs. Click each module below to view detailed topics, live coding projects, and industry tools.
01
Advanced SQL, Dimensional Modeling & Lakehouse Architecture
16 Hours
Advanced SQL, Dimensional Modeling & Lakehouse Architecture
Master modern data modeling, dimensional schemas, Medallion Architecture, and advanced SQL analytical queries.
Core Technical Topics & Competencies Covered:
- โAdvanced SQL: Window Functions, CTEs, Recursive Queries & Query Execution Plans
- โDimensional Modeling: Star Schemas, Snowflake Schemas, Fact vs Dimension Tables
- โSlowly Changing Dimensions (SCD Type 1, Type 2, Type 3)
- โData Lake vs Data Warehouse vs Data Lakehouse Paradigms
- โThe Medallion Architecture: Bronze (Raw), Silver (Cleaned), Gold (Aggregated Business Data)
02
Big Data Processing with Apache Spark & PySpark
20 Hours
Big Data Processing with Apache Spark & PySpark
Scale data transformations across distributed clusters using PySpark and understand low-level execution internals.
Core Technical Topics & Competencies Covered:
- โSpark Architecture: Driver, Executors, Cluster Managers, RDDs vs DataFrames
- โPySpark DataFrame API: Transformations, Actions, Filtering, Aggregations & Joins
- โSpark Optimization: Catalyst Optimizer, Tungsten Execution Engine & Adaptive Query Execution (AQE)
- โPartitioning Strategies, Bucketing & Eliminating Data Skew & Shuffling
- โSpark Structured Streaming: Processing Live Event Streams with Watermarking
03
Databricks Delta Lake & Snowflake Cloud Lakehouse
20 Hours
Databricks Delta Lake & Snowflake Cloud Lakehouse
Build enterprise production lakehouses using Databricks Delta Lake and Snowflake cloud warehousing.
Core Technical Topics & Competencies Covered:
- โDelta Lake ACID Transactions: Time Travel, Schema Enforcement & Schema Evolution
- โOPTIMIZE, Z-Ordering & Compaction for Sub-Second Delta Query Performance
- โDatabricks Unity Catalog: Centralized Governance, Access Control & Data Lineage
- โSnowflake Architecture: Storage vs Compute decoupling, Virtual Warehouses & Micro-partitions
- โSnowflake Features: Snowpipe Continuous Ingestion, Streams & Tasks, Zero-Copy Cloning
04
Data Transformation & CI/CD with dbt (Data Build Tool)
16 Hours
Data Transformation & CI/CD with dbt (Data Build Tool)
Treat data transformations as modern software engineering code with modular SQL, automated testing, and CI/CD.
Core Technical Topics & Competencies Covered:
- โWhy dbt: Modularity, Version Control, Automated Documentation & Lineage DAGs
- โdbt Models: Views, Tables, Incremental Models & Ephemeral CTEs
- โJinja Templating, Macros and Packages (dbt-utils, dbt-expectations)
- โData Quality Testing: Generic Tests, Custom Singular Tests, Freshness Checks
- โdbt Docs Generation and Deploying dbt Workflows in CI/CD
05
Event-Driven Streaming with Apache Kafka & Orchestration with Airflow
16 Hours
Event-Driven Streaming with Apache Kafka & Orchestration with Airflow
Capture real-time event streams and orchestrate resilient multi-dependency data pipelines.
Core Technical Topics & Competencies Covered:
- โApache Kafka Architecture: Topics, Partitions, Producers, Consumers & Consumer Groups
- โSchema Registry & Avro Serialization for Resilient Event Ingestion
- โKafka Connect: Sourcing Data from RDBMS (CDC with Debezium) into S3/Lakehouse
- โApache Airflow Fundamentals: DAGs, Operators, Sensors, Hooks, XComs
- โScheduling, Retries, SLAs, and Production Airflow Deployment with Docker
06
AI-Augmented Data Pipelines & Vector Data Ingestion
12 Hours
AI-Augmented Data Pipelines & Vector Data Ingestion
Integrate LLMs into ETL pipelines for automated data cleaning, classification, and vector database ingestion.
Core Technical Topics & Competencies Covered:
- โAI in ETL: Using LLMs for Entity Resolution, Data Cleansing & Complex Schema Inference
- โVector Lakehouse Pipelines: Automatically Chunking, Embedding & Ingesting Data into Vector Stores
- โSnowflake Cortex & Databricks AI Functions for In-Database Generative AI
- โData Quality Monitoring with Great Expectations & Soda Core
- โCareer Preparation: Technical Architecture System Design Interviews for Big Data & AI Engineers
Where Our Varanasi Students Get Hired
Over 500+ global enterprises and innovative unicorns hire directly from 4Achievers programs.
Frequently Asked Questions (Varanasi)
Everything you need to know about fees, batch timings, placement support, and prerequisites.
Why choose 4Achievers for Data Engineering with AI in Varanasi?
4Achievers provides 100% placement assurance, dedicated offline labs with high-speed development machines, real-world live projects, and personal 1-on-1 mentor guidance from working senior engineers.
What is the course duration and batch schedule?
The program spans 14 Weeks with both weekday regular batches (Mon-Fri) and weekend tracks (Sat-Sun) specifically designed for working professionals and university students.
Is there 100% placement support provided in Varanasi?
Yes! Our dedicated Corporate Placement Cell coordinates guaranteed interview drives, resume redesign workshops, and mock technical grilling until you secure your desired job offer.