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The Complete

The DataFoundry

Become a modern data architect for the AI and agentic era. Design and build production-grade, cloud-native data platforms, not just pipelines, that carry analytics, machine learning and the applications built on top of them.

A hands-on path across SQL, Python, orchestration, streaming, warehouses and multi-cloud architecture, building the judgment to choose the right pattern for the problem rather than the syntax for the tool.

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44 chapters10 partsFree to read
The Complete

The Data Foundry

MorpheraLabsForty-four chapters : foundations to AWS, Azure and Google Cloud

Why this book

Written to be worked through, not skimmed

01

Grounded in real systems

Every chapter opens on a concrete scenario before it defines anything. You learn not just how a tool works but where it belongs, and when reaching for it is the wrong call.

02

One path, in order

Forty-four chapters across ten parts, numbered and sequential. You always know where you are and what comes next, instead of assembling a curriculum out of disconnected tutorials.

03

Written for the current stack

An entire part is given to agentic workflows: coding agents, LLM-assisted pipelines, and the judgment to review what they produce. The skills that separate the next decade from the last.

Curriculum

Ten parts, foundations to cloud

Built from the live instructor-led course. Chapter numbers restart inside each part, so a part can grow without renumbering the rest of the book.

  1. 00OrientationThinking Like a Data EngineerThe mindset and systems view to build before going deep into any tool.3 chapters
  2. 01FoundationsSQL: The Language of DataQuerying, joins, views, aggregation, subqueries, CTEs, window functions, pivots and schema design.10 chapters
  3. 02ProgrammingPython: The Engineer's ToolLanguage fundamentals through file handling, error handling, NumPy and Pandas.7 chapters
  4. 03PipelinesOrchestration: Apache AirflowWhy pipelines need a scheduler, how Airflow is built, and running it locally.3 chapters
  5. 04DeliveryEngineering PracticesContainers, continuous integration and the shell work that holds a platform together.3 chapters
  6. 05AI-assistedAgentic Data EngineeringCoding agents, LLM-assisted pipelines and where judgment still has to be yours.3 chapters
  7. 06ModellingCloud Warehousing: Snowflake and dbtDimensional modelling, slowly changing dimensions, and analytics engineering in production.5 chapters
  8. 07StreamingReal-Time Data: Apache KafkaWhen streaming earns its complexity, and change data capture in practice.3 chapters
  9. 08CloudAWS for Data EngineersIdentity, warehousing, event-driven processing and infrastructure as code.4 chapters
  10. 09CloudAzure for Data EngineersMedallion architecture with Data Factory and Databricks, Fabric and Synapse.3 chapters

What you build

Pipelines that run, not diagrams that explain

Every part ends in something executable: a model that builds, a DAG that schedules, a warehouse that loads. The commands below are the shape of the work.

Open the book
~/the-data-foundry

$ dbt run --select orders

✓ Completed successfully

$ python pipelines/transform.py

✓ 48,213 rows loaded to warehouse.orders_clean

$ airflow dags trigger daily_pipeline

✓ DAG run succeeded

Authors

Written by the engineers who teach it

Qasim HassanSenior Data EngineerLinkedIn Ayan HussainData EngineerLinkedIn Abdullah KhanData EngineerLinkedIn Haniya MaqsoodSenior Data EngineerLinkedIn

Voices

Real results, real voices​

A few of the people who have come through Cloud Data Engineering, on what the programme was actually like.

  • Ayan Hussain

    Cloud Data Engineering

    I had a great learning experience. The content is up to date with current industry needs and covers multiple cloud architectures, including AWS, Azure, and Snowflake. The course also focuses on solving complex problems using cost-optimized solutions. The "Data Foundry" books helped me tremendously in building my theoretical knowledge and keeping pace with the practical content covered in the classes. Overall, I am highly grateful for the opportunity to learn and grow through this course. I am now applying the data engineering concepts and skills I learned in my professional work. Appreciations to the team behind this work!

  • Irtaza Azeem

    Cloud Data Engineering

    I was part of the Salani Data Engineering batch, and it was a very valuable learning experience for me. I learned SQL, ETL pipelines, and gained hands-on experience with AWS through various projects. The skills I gained have been extremely useful throughout my professional journey. They helped me during my first internship at the State Bank of Pakistan and continue to help me in my current role as a Machine Learning Engineer at Bank Alfalah, especially with SQL and ETL pipelines. I am truly thankful to Sir Qasim for giving me this opportunity and helping me build a strong foundation in Data Engineering. It has definitely been one of the most useful learning experiences for me.

  • Jahanzaib Ali

    Cloud Data Engineering

    I had the privilege of being taught by Sir Qasim Hassan during the Cloud Data Engineering bootcamp at Saylani, and the impact of his mentorship on my career has been immense. Sir Qasim does not just teach theory; he breaks down complex architectural patterns, modern data pipelines, and cloud systems with exceptional clarity and real-world relevance. ​His focus on industry-grade engineering practices gave me the technical foundation and problem-solving mindset required to scale high-impact systems. The concepts and discipline he instilled are directly responsible for my growth into a Full-Stack Engineer and Team Lead at Bluehawke (Al Habib Groups). Anyone fortunate enough to learn under Sir Qasim is learning from an outstanding mentor and an exceptional engineer.

  • Rayyan Sajidd

    Cloud Data Engineering

    I had the opportunity to study Cloud Data Engineering under Sir Qasim Hassan and it was one of the best descisions i took. The course from start to finish had everything a person needed to know in order to not just be familiar with CDE but the ways of Sir Qasim led us to have a practical implementation of it. The course itself is very fun to study and the ways of teaching was itself a huge help for anyone who knew nothing about it in he beginning but you come out a polished technical person. My personal experience was great with Saylani for when I took this course and I would higly recommend it to anyone who is thinking about joining. As of right now I'm working as an AI Engineer and the use of clouds has become much simpler because of everything i learned from this course.

  • Danial Aneeq Ahmed

    Cloud Data Engineering

    The course gives you not only solid technical knowledge but also practical ways to handle real problems that appear in industry. Its clear lessons and hands-on work made complex cloud data topics easy to apply. I finished feeling better prepared and more confident in my skills.

  • Syed Uzair Shah

    Cloud Data Engineering

    The Cloud Data Engineering programme was a great learning experience, providing hands-on skills in Python, Pandas, NumPy, web scraping, Snowflake, Docker, and modern data engineering tools. Real-world projects strengthened my understanding of data pipelines and cloud solutions while preparing me for a career in Cloud Data Engineering

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SQL through cloud architecture, published and free to read today. New parts land as they are finished.

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