Stay in the loop

Get notified when new paths are added

Defence Forces, Psychology, Architecture, Agriculture, and more are coming. One email a month at most. No spam.

CareerMaps

Home Roadmaps

All Careers After 10th After 12th Skills Popular Careers Highest Paying Jobs

BrainMap

About Us Mission & Vision Contact Feedback

Stay in the loop

Get notified when new paths are added

Defence Forces, Psychology, Architecture, Agriculture, and more are coming. One email a month at most. No spam.

Back to All Roadmaps

Data Engineering

Build robust data pipelines and scale databases for analytics and AI.

Build robust data pipelines to collect, store, and process massive scale data for analytics and machine learning.

Estimated Time: 4-8 Months

Starting Salary: ₹7L - ₹35L+ per annum

Quick Overview

Database Mastery

Advanced SQL
Data Modeling
Relational vs NoSQL
Data Warehousing

Data Processing (ETL)

Python & Pandas
Apache Spark
Hadoop Ecosystem
Airflow (Orchestration)

Real-time Streaming

Apache Kafka
Event-driven Arch
Streaming Analytics
Data Lakes

Cloud Platforms

AWS/GCP Context
Snowflake / BigQuery
Security & Governance
Infrastructure as Code

Pro Tips for Success

SQL is king. Advanced SQL (window functions, CTEs) is non-negotiable.
Understand distributed systems. Processing terabytes of data requires a different mindset.

What Employers Want

Ability to write robust, maintainable ETL pipelines.
Knowledge of data orchestration tools like Apache Airflow.

Detailed Study Modules

Databases & Data Warehousing

Master SQL, understand relational vs NoSQL databases, and learn columnar storage (Snowflake, BigQuery).

Recommended Resources

Database Design Guide

Action Items & Checklist

Design a normalized SQL schema
Write complex JOIN queries
Understand differences between OLTP and OLAP

Data Processing & ETL

Learn Apache Spark, Hadoop, and Airflow to process large datasets and orchestrate ETL (Extract, Transform, Load) pipelines.

Recommended Resources

Apache airflow tutorial

Action Items & Checklist

Write an Airflow DAG
Process data using PySpark
Load transformed data into a Data Warehouse

Streaming & Cloud Data Platforms

Handle real-time data using Apache Kafka. Deploy your data infrastructure on AWS or GCP.

Recommended Resources

Kafka Beginners Tutorial

Action Items & Checklist

Set up a Kafka cluster
Write a Kafka Producer and Consumer
Deploy an ETL pipeline on AWS Glue

Frequently Asked Questions

Is Data Engineering the same as Data Science?

No. Data Engineers build the pipelines and infrastructure that Data Scientists use to retrieve and analyze data.

Explore Related Paths

Data Engineering

Build robust data pipelines and scale databases for analytics and AI.

Build robust data pipelines to collect, store, and process massive scale data for analytics and machine learning.

Estimated Time: 4-8 Months

Starting Salary: ₹7L - ₹35L+ per annum

Quick Overview

Database Mastery

Advanced SQL
Data Modeling
Relational vs NoSQL
Data Warehousing

Data Processing (ETL)

Python & Pandas
Apache Spark
Hadoop Ecosystem
Airflow (Orchestration)

Real-time Streaming

Apache Kafka
Event-driven Arch
Streaming Analytics
Data Lakes

Cloud Platforms

AWS/GCP Context
Snowflake / BigQuery
Security & Governance
Infrastructure as Code

Pro Tips for Success

SQL is king. Advanced SQL (window functions, CTEs) is non-negotiable.
Understand distributed systems. Processing terabytes of data requires a different mindset.