Career & Background Oct 30, 2026

Who Is Asim Raza? My Journey, Work and Career in Data Engineering

My name is Asim Raza. I am a Data Engineer from Gojra, Punjab, Pakistan, and I build data pipelines, data processing workflows and analytics systems using Python, SQL, PySpark, Databricks, Delta Lake and cloud technologies.

I created Asim Builds as my professional space to document what I build, share my technical work and make it easier for people to understand my background.

My interest in Data Engineering comes from wanting to understand what happens behind applications. An application does more than display information. It collects data, communicates with services, stores records and depends on systems that process information in the background. I wanted to understand how those systems work together.

That curiosity gradually became my direction in Computer Science and Data Engineering.

Today, I focus on building complete systems that solve practical problems. I enjoy connecting different components, troubleshooting issues and turning raw information into structured datasets that can support analysis.

This page brings together my background, education, experience, projects, technical skills and professional interests.

My Background and Education

I am pursuing a Bachelor of Science in Computer Science at Virtual University of Pakistan, where I began my studies in 2022.

Studying Computer Science has given me a foundation for understanding programming, databases, software systems and the technical concepts behind modern applications.

My interest gradually moved toward the data side of these systems. I became particularly interested in how information is collected, stored, transformed, validated and made available for reporting and decision-making.

I also learned through practical development work. My earlier experience with WordPress development exposed me to website functionality, databases and the technical requirements of digital products.

Rather than limiting my learning to individual programming exercises, I started building projects that connect several parts of a complete data workflow.

Why I Chose Data Engineering

The question that initially attracted me to Data Engineering was simple:

How do the data systems behind applications actually work?

I wanted to understand what happens after a user interacts with an application. Where does the information go? How is it stored? What happens when data arrives in an inconsistent format? How do organizations turn large amounts of information into something useful?

These questions introduced me to Python, SQL, databases, APIs and data processing.

What I enjoy most about this field is building complete systems and solving practical problems. I like understanding the source of the data, designing an ingestion process, organizing storage, applying transformations and checking whether the final output is reliable.

For me, Data Engineering is not simply about moving data from one location to another. It is about creating a dependable process that makes data useful.

My long-term goal is to build a strong career in Data Engineering internationally, contribute to engineering teams and continue developing my knowledge of cloud data platforms, distributed processing and modern data architecture.

What I Build: My Data Engineering Projects

I believe practical projects are one of the best ways to demonstrate technical understanding. My main focus is building end-to-end data workflows that bring ingestion, storage, transformation, data quality and analytics together.

1. Job Market Intelligence Platform

GitHub repository: https://github.com/asimraza3768/job-market-intelligence

The Job Market Intelligence Platform is one of my main Data Engineering projects. It collects job listings from a REST API and processes them into analytics-ready datasets and dashboards.

I designed the architecture around the following workflow:

JobsPipe API → Databricks Workflow → Amazon S3 Raw Landing → Bronze Delta → Silver Delta → Gold Delta → Databricks AI/BI Dashboard

The project uses Python, SQL, PySpark, Databricks, AWS S3, Delta Lake and REST API integration.

My engineering work includes:

  • REST API ingestion and cursor-based pagination
  • Raw JSON data landing in Amazon S3
  • Bronze and Silver Delta Lake processing
  • MERGE-based upserts
  • Nested JSON processing
  • PySpark transformations
  • Silver-layer data quality validation
  • Databricks Workflow orchestration
  • Gold analytics tables and dashboard development

The documented project results include:

  • More than 400 job listings analyzed
  • Five cities represented
  • Four Databricks Workflow tasks or notebooks
  • Three Medallion Architecture layers
  • Six Gold analytics tables
  • One raw S3 landing layer
  • One Databricks AI/BI dashboard

The data quality checks cover required fields, duplicate records, salary validation, timestamps, remote-work values and country codes. The Gold layer supports analysis of skill demand, country markets, skill gaps, skill co-occurrence and profile skill coverage. Building this platform helped me understand how API integration, cloud storage, distributed transformations, data validation and analytics fit together in a complete data engineering workflow.

2. Weather Data Engineering Pipeline

This project collects weather information from the OpenWeather API and transforms it into structured datasets for analysis. Its architecture follows a Medallion-style workflow:

OpenWeather API → Bronze Delta → Silver PySpark → Data Quality → Gold Analytics → Dashboard

I developed the pipeline using Python, PySpark, SQL, Databricks and Delta Lake. The pipeline covers five cities: Gojra, Faisalabad, Lahore, Islamabad, and Karachi.

The project uses three main tables:

  • weather.bronze.bronze_weather
  • weather.silver.silver_weather
  • weather.gold.daily_weather_summary

The transformations include Unix timestamp conversion, weather-time processing, visibility conversion to kilometers, wind-speed conversion and wind-direction transformation. The purpose is to take external API responses and organize them into structured, validated and dashboard-ready datasets.

3. Sentinel AI

Sentinel AI is a hackathon project focused on disaster management and climate-related risk analysis. I contributed as Team Lead and Data Engineer. The project combines data and machine learning components to support risk assessment and related workflows.

The technology stack includes Python, FastAPI, XGBoost, Open-Meteo and other application components. The project was built for the Qabil Bano Pakistan national hackathon. Our team advanced through two stages, with the regional round pending at the time of writing. This project gave me an opportunity to work with a team, contribute to a larger application and explore how data and machine learning can support practical problem-solving.

4. Online Grocery Management System

I also worked on an Online Grocery Management System as a university project. It was developed using PHP and MySQL and involved building application functionality around grocery management. This project gave me experience with relational databases, application logic and the way software systems organize and manage information.

You can explore more of my work through my GitHub profile.

My Technical Skills and Tools

I focus on technologies that help me build and maintain data workflows.

  • Programming: Python, SQL, PHP
  • Data Engineering: ETL and ELT, Data pipeline development, Data integration, Data quality validation, Data transformation, Data modeling, Dimensional modeling, Star schema
  • Big Data and Processing: Apache Spark, PySpark
  • Cloud and Data Platforms: Databricks, AWS S3, Delta Lake, Unity Catalog, Databricks Workflows, Databricks AI/BI
  • Databases: PostgreSQL, MySQL, MongoDB
  • APIs and Integration: REST APIs, API ingestion, Cursor-based pagination, JSON processing
  • Development and Engineering Tools: Git and GitHub, Docker, GitHub Actions, CI/CD, Python testing, Pandas, Scikit-Learn

I am also developing my understanding of tools and technologies such as Apache Airflow, dbt, Kafka, Hadoop and Snowflake. My experience varies by tool, so I distinguish hands-on project work from coursework and ongoing learning. I prefer understanding how technologies fit into a complete system rather than collecting tool names without practical context.

My Professional Experience

My experience includes technical work, freelance development, administration and customer-facing responsibilities.

  • PNP — Digital Department Intern (Islamabad | Oct–Nov 2026): Gaining experience in digital and media-related work, including news writing, fact-checking, and media monitoring.
  • Freelance WordPress Developer (Approx 4 years): Built and maintained websites, troubleshooting, client communication, and delivering work according to project requirements.
  • Lab Administrator Intern — Virtual University of Pakistan (Gojra | Mar–Aug 2023): Supported day-to-day operations of a university computer lab, setting up software, and troubleshooting connectivity issues.
  • Front Counter Associate — Bonsaii Restaurant (May–Aug 2023): Gained experience in customer interaction, communication, and organization in a fast-paced environment.

Certifications and Professional Learning

I continue to develop my technical knowledge through courses, certifications and virtual job simulations. My learning includes certifications from IBM (Data Engineering, Python for Data Science), DataCamp (Data Engineer in Python, SQL, Airflow, ETL/ELT), and Job Simulations with BCG, Deloitte Australia, PwC US, and KPMG US.

Job simulations and virtual internships are learning experiences, not employment positions. I include them to document the additional skills and professional exposure I have developed.

Beyond Technology

Although Data Engineering is my main professional direction, I have interests outside programming and technical work. I enjoy writing, poetry, singing, music, reading and exploring new ideas. I also value communication and the ability to explain information clearly. My experience with writing and media-related activities gives me another perspective on how information is researched, organized and presented.

I believe technical ability and communication complement each other. Building a useful system matters, but being able to explain how it works and why it matters is important too.

What I Am Working Toward

My long-term goal is to establish a strong international career in Data Engineering. I want to keep improving my skills in cloud data platforms, distributed processing, data architecture, orchestration and reliable pipeline development.

I approach this goal by building projects, documenting my work, strengthening my technical foundation and staying open to new opportunities. I do not see learning as something that ends after completing a course or project. Every system I build gives me another opportunity to understand a problem more deeply and improve how I approach it.

Connect With Asim Raza

If you are a recruiter, hiring manager, Data Engineer or technology professional interested in my background, projects or potential collaboration, you can connect with me through the following profiles:

Last updated: October 30, 2026.