Building production-style data pipelines across AWS • GCP • Microsoft Fabric • SAP
I'm a Software Engineering student and Data Engineer focused on building reliable, scalable, and analytics-ready data systems.
My work covers the complete data lifecycle:
Data Sources → Ingestion → Bronze → Silver → Gold → Data Warehouse → Analytics
I enjoy solving practical data engineering problems involving ETL/ELT, batch processing, near-real-time streaming, orchestration, data quality, cloud storage, warehousing, and analytics.
- 🎓 BS Software Engineering — SMIU, Karachi
- ☁️ Focus: Cloud Data Engineering
- ⚡ Core Area: Batch & Streaming Data Pipelines
- 🏗️ Architecture: Medallion, Lakehouse & Data Warehouse
- 📊 Analytics: Power BI, SAP Analytics Cloud & Streamlit
- 🚀 Open to: Junior / Associate Data Engineering opportunities
Enterprise data and analytics case study for a large elevator/manufacturing environment with fragmented operational data.
Highlights
- Integrated data across ERP, Procurement, MES, Elevator IoT, and Maintenance
- Designed relationships across customers, elevators, locations, production, and service operations
- Built analytical models using SAP Datasphere
- Designed KPI and visualization layer using SAP Analytics Cloud
- Worked with large-scale elevator sensor, alarm, and maintenance datasets
Tech: SAP Datasphere SAP Analytics Cloud SAP ERP AWS S3 Python SQL
Serverless forecasting solution built to predict Air Quality Index up to 3 days ahead across six major cities in Pakistan.
Highlights
- Automated hourly weather and pollution ingestion
- Historical backfill pipeline
- Bronze → Silver → Gold data lifecycle
- Separate forecasting models per city and forecast horizon
- Ridge Regression, Random Forest, and TensorFlow models
- RMSE, MAE, and R² evaluation
- Cloud Run API + Streamlit Dashboard deployment
- Scheduled and automated pipeline execution
Tech: GCP BigQuery dbt TensorFlow Python Cloud Run Streamlit
Production-style pipeline combining batch schedules with near-real-time cricket updates.
Highlights
- Batch + near-real-time ingestion
- Duplicate handling across repeated ingestion
- PySpark cleaning and deduplication
- dbt modeling with Amazon Athena
- Bronze → Silver → Gold architecture
- Kestra orchestration
- Terraform infrastructure
- Dockerized development workflow
Tech: AWS S3 Lambda Glue PySpark Athena dbt Kestra Terraform Docker
Batch analytics pipeline ingesting aviation data from the OpenSky Network API.
Highlights
- Automated ingestion every 30 minutes
- Bronze → Silver → Gold architecture
- Apache Airflow orchestration
- Retry logic and idempotent task design
- Snowflake Gold layer
- Power BI analytics
Tech: Airflow Python Snowflake Docker Power BI
End-to-end analytics pipeline built inside Snowflake.
Highlights
- Raw booking ingestion into Bronze
- Data quality transformations in Silver
- Business aggregations in Gold
- Cleaned invalid emails, negative values, and inconsistent statuses
- Analytics through Snowsight
Tech: Snowflake SQL Medallion Architecture Snowsight
Event-driven data pipeline designed for serverless ingestion and transformation.
Highlights
- JSON → Parquet transformation
- S3 partitioning
- Lambda-based processing
- Automated schema discovery using Glue
- Query-ready datasets using Athena
Tech: AWS Lambda Amazon S3 AWS Glue Athena Python Parquet
- Building production-style batch and streaming pipelines
- Working with Kafka, PySpark, dlt, BigQuery, dbt, Kestra, Bruin, and Docker
- Hands-on work with cloud-based Medallion architectures
- Working under the mentorship of Sir Qasim Hassan and Sir Ayan Hussain
- Built an end-to-end AQI Forecasting & MLOps platform
- Worked on ingestion, feature engineering, machine learning, and cloud deployment
- Used BigQuery, dbt, TensorFlow, Cloud Run, APIs, and Streamlit
Jan 2026 – Mar 2026 | Remote
- Built ETL pipelines using Python, Pandas, and NumPy
- Automated data validation and quality checks
- Standardized datasets across multiple workflows
- Prepared analytics-ready transformed datasets
Microsoft Certified: Fabric Data Engineer Associate
DP-700 — Implementing Data Engineering Solutions Using Microsoft Fabric
| Degree | Institution | Duration |
|---|---|---|
| BS Software Engineering | Sindh Madressatul Islam University (SMIU), Karachi | 2023 – 2027 |
| Intermediate — Pre-Engineering | Govt. Boys Degree College, Naudero | 2019 – 2021 |
- Big Data Fundamentals with PySpark — DataCamp
- Snowflake Hands-On Essentials
- Python — DataCamp
- Data Analytics — Deloitte
- GenAI Data Analytics — Tata
Open to Junior / Associate Data Engineer roles, internships, collaborations, and Data Engineering projects.
Python • SQL • Spark • Kafka • AWS • GCP • Microsoft Fabric • SAP • Snowflake • dbt
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