About This Program
An engineering-centered program for building trustworthy data systems at scale. Learners progress from relational modeling and Python pipelines to distributed processing, event streaming, cloud lakehouse architecture, governance, observability, and a production-grade capstone evaluated for correctness, reliability, cost, and maintainability.
What You'll Get
15+ Production Data Pipeline Projects
Batch and Real-Time Architectures
AWS, Azure and GCP Data Services
Data Quality and Governance Practice
Architecture Reviews and Career Mentorship
Program Curriculum
1Programming & Systems Foundations4 Weeks
Key Topics:
Python for Data Engineering
Advanced SQL and Query Reasoning
Linux, Shell and Process Automation
Git Workflows and Code Review
Data Structures and Complexity Fundamentals
Networking, APIs and Serialization Formats
2Relational Databases & Data Modeling4 Weeks
Key Topics:
Relational Algebra and Database Internals
Normalization and Transaction Design
Dimensional Modeling and Star Schemas
Indexes, Execution Plans and Query Tuning
Slowly Changing Dimensions
PostgreSQL Data Modeling Project
3Data Ingestion, ETL & Orchestration5 Weeks
Key Topics:
ETL, ELT and Change Data Capture
Idempotent and Incremental Pipeline Design
Apache Airflow DAG Architecture
Scheduling, Backfills and Dependency Management
Schema Evolution and Data Contracts
Failure Recovery and Pipeline Observability
4Warehouses, Lakes & Lakehouse Architecture5 Weeks
Key Topics:
Data Warehouse Architecture
Object Storage and Data Lake Design
Parquet, Avro and Columnar Storage
Table Formats: Delta Lake and Apache Iceberg
dbt Modeling, Testing and Documentation
Cost-Aware Analytics Architecture
5Distributed Data Processing5 Weeks
Key Topics:
Distributed Systems Fundamentals
Apache Spark Architecture and Execution
DataFrames, Spark SQL and PySpark
Partitioning, Shuffles and Join Strategies
Performance Tuning and Resource Management
Large-Scale Batch Processing Project
6Streaming & Event-Driven Data Systems4 Weeks
Key Topics:
Event Streaming Concepts and Delivery Semantics
Apache Kafka Topics, Partitions and Consumer Groups
Stream Processing and Windowing
Late Data, Watermarks and State Management
Schema Registry and Event Contracts
Real-Time Analytics Pipeline
7Cloud Data Platforms5 Weeks
Key Topics:
AWS S3, Glue, Redshift and EMR
Azure Data Factory, Synapse and Databricks
GCP BigQuery, Dataflow and Dataproc
Cloud IAM, Encryption and Network Controls
Serverless Data Processing Patterns
Cloud Architecture and Cost Optimization
8Data Quality, Governance & Reliability4 Weeks
Key Topics:
Data Profiling and Quality Dimensions
Automated Validation and Reconciliation
Metadata, Catalogs and Lineage
Master Data and Reference Data Management
Privacy, Retention and Access Governance
Service-Level Objectives for Data Products
9DataOps, Capstone & Career Readiness4 Weeks
Key Topics:
Docker and Infrastructure as Code
CI/CD for Data Pipelines
Monitoring, Alerting and Incident Response
End-to-End Data Platform Capstone
Architecture Defense and Portfolio Documentation
SQL, Python and System Design Interviews
Course Fee
₹90,000/ 9 Months
Limited seats available for next batch.