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Intermediate 12 weeks 💰 Fee · PKR 20,000

Data Engineering

Move and transform data at scale — SQL, Airflow, Spark, and modern warehouses.

Program fee

PKR 20,000

or up to 2 installments

Stack: SQL Airflow Spark BigQuery Snowflake dbt ETL Kafka PySpark

Live virtual classes

Every evening at 9–11 PM (PKT), plus weekend deep-dives

No prerecorded lectures. Every session is live with a mentor — you ask questions, write code on the call, and get feedback in real time. Weekend sessions are extended deep-dives where you build the week's project end-to-end with the cohort.

Weeknight classes

Monday to Friday · 9–11 PM PKT. Concepts, walkthroughs, mentor Q&A. After your day job or classes.

Weekend deep-dives

Saturday & Sunday · extended hands-on sessions. Ship a working project every weekend with the cohort.

🎥 100% live · Zoom & Google Meet 📼 Recordings if you miss 💬 24h mentor reply on chat

About this program

Data engineering is the highest-leverage tech career nobody talks about. Every company is drowning in data and the people who can turn it into reliable pipelines and warehouses earn senior-backend money without the interview hell. Live sessions weeknights 9–11 PM PKT. Weekend deep-dives are where you build the week's pipeline end-to-end — Airflow DAGs running, dbt models tested, Spark jobs reading at scale.

What you'll build

Real projects · not toy exercises

🗃

50 SQL Problems Solved

Window functions, CTEs, performance — interview-grade.

⏱

Daily Airflow DAG

A production-style Airflow pipeline running daily with retries.

🏗

Modeled Data Warehouse

dbt models + tests on top of BigQuery or Snowflake.

⚡

PySpark Job

Spark transformation reading from object storage at scale.

🌊

Streaming POC

Kafka producer/consumer + a downstream sink.

Who this program is for

If any of these sound like you, you're in the right place 👋

✓ You're a SQL analyst wanting to move into engineering.

✓ You're a backend engineer interested in data infrastructure.

✓ You want a data-engineer role at a startup or BI consultancy.

Course outline

What you'll learn

5 modules · 25 topics · hands-on the whole way.

SQL Mastery

Joins & aggregations
Window functions
Indexes & query plans
Schema design
Performance tuning

Python for Data

Pandas at scale
Working with APIs
Pydantic & validation
Pytest for data
Pyarrow & Parquet

Pipelines

Airflow DAGs
Scheduling & retries
Sensors & operators
Data quality checks
Backfills

Warehousing

BigQuery / Snowflake basics
dbt models & tests
Slowly changing dimensions
Cost optimisation
Semantic layer

Big Data Tools

Spark fundamentals
PySpark transformations
Streaming with Kafka
Lakehouse architectures
Delta / Iceberg basics

Your roadmap

Week by week, step by step

A clear path — not vibes. You'll know exactly what to ship at every checkpoint.

SQL mastery

Weeks 1-3

Deliverable: Solved 50 SQL problems + 1 schema design

Pipelines with Airflow

Weeks 4-6

Deliverable: Daily DAG running in cloud

Warehouse + dbt

Weeks 7-9

Deliverable: Modeled data warehouse with tests

Spark + streaming

Weeks 10-12

Deliverable: PySpark job + streaming POC

What changes after

By the last week, you can…

🎯

Design and ship reliable ETL pipelines on Airflow.

🎯

Build a modeled data warehouse with dbt that analysts trust.

🎯

Read execution plans and tune slow SQL by yourself.

🎯

Run PySpark jobs at scale and reason about partitioning.

Ready to start Data Engineering?

Free forever. Mentor-led. Real projects. The kind of program you'd pay for — except you don't have to.

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