Senior Data Engineer & Startup Founder

Summary

Lead Data Engineer (Founder) with a unique blend of startup ownership and deep technical execution, having built and scaled end-to-end data platforms from scratch on AWS. Expert in designing real-time data pipelines, NoSQL/SQL data models, and high-throughput ingestion systems handling hundreds of millions of records monthly. Delivered low-latency analytics, trading data systems, and BI solutions, while optimizing performance by up to 40%. Combines hands-on engineering expertise with system design and leadership, driving scalable data solutions in fast-paced environments. Experience

HyperBlock Studio Inc. Canada

Founding Data Engineer 02/2024 - Present

Architected and scaled cloud-native data infrastructure on AWS (S3, Lambda, RDS), supporting real-time financial data processing.

Engineered high-performance NoSQL data models in MongoDB for high-frequency trading datasets, supporting millions of records/day and reducing query latency by ~25%.

Built scalable data ingestion pipelines integrating APIs and market feeds, processing real-time & batch data streams

(100K+ events/day) with high reliability.

Enhanced MongoDB aggregation pipelines and query performance, improving data retrieval speed by 30% and enabling faster analytics.

Structured analytics-ready data layers for dashboards, reporting, and trading insights. Streamlined data transformation workflows using Python, reducing manual processing effort by 50%+ and improving pipeline efficiency.

Integrated Elasticsearch for advanced indexing and search, enabling sub-second query response times across large-scale datasets.

Established data validation, governance, and monitoring frameworks, achieving 99%+ data accuracy and significantly reducing data inconsistencies.

Partnered with cross-functional teams to deliver data-driven APIs and analytics features, supporting production systems used by thousands of users.

Afiniti Lahore, Pakistan

Associate Data Engineer 03/2021 - 02/2024

Delivered scalable ETL pipelines using Talend, processing real time and batch datasets (500M+ records/month). Transitioned legacy ETL workflows to Dockerized Apache Airflow, reducing job failures by 30%. Analysed and created robust ingestion and transformation frameworks using Talend and Python, processing 500M+ records/month with high scalability and fault tolerance. Created Python-based data validation and anomaly detection systems, reducing data errors by 30%+ and improving overall data reliability.

Accelerated SQL query performance (PostgreSQL, Greenplum), reducing execution time by up to 40%. Automated reporting pipelines, saving 70+ hours/month and improving SLA adherence to 95%. Delivered data models supporting real-time analytics and executive dashboards, enabling faster decision-making for business stakeholders and reducing reporting latency by 20%. Collaborated with DevOps to implement monitoring and alerting systems, reducing downtime by 35%. Led a team of 4 engineers, ensuring 100% on-time delivery across 3 projects. Enforced GDPR-compliant data security and access controls across AWS environments, ensuring 100% compliance and secure handling of sensitive data.

Allied Bank (Head Office) Lahore, Pakistan

Data Integration Officer 11/2019 - 03/2021

Maintained ETL pipelines processing 15M+ records/day, ensuring 99.99% availability. Coordinated with IBM on Hadoop migration initiatives for enterprise data modernization. Enabled WhatsApp banking analytics pipelines for 10M+ customers. Developed SOA/e-SOA automation pipelines, saving ~500 man-hours/year. Supported real-time data processing using Spark, Hive, and MapReduce. Ahmad Waleed Hamid

+923********* *****************@*****.*** Lahore, Pakistan Skills

ETL Development, SQL Optimization, PostgreSQL, MSSQL, PL/SQL, Data Warehousing, Star / Snowflake Schema, Cloud Platforms, AWS, Team Leadership, Stakeholder Management, Python, AWS, Docker, ETL/ELT Pipelines, Data Pipelines, Data Ingestion, Data Transformation, Workflow Orchestration, PostgreSQL, Greenplum, MongoDB, Data Warehousing, Data Modeling, Query Optimization, Scalability, Performance Tuning Education

FAST - National University of Computer and Emerging Sciences Islamabad, Pakistan BS Computer Science 05/2019

Fall Detection Using Kinect 2.0: R&D project using C#, Python, Android Studio integrated with Microsoft Kinect V2 to detect elderly falls and trigger mobile alerts.

Nash Equilibrium Simulation: Developed a simulation model applying Game Theory to determine equilibrium points, supporting both manual and auto data input.

IRIS Recognition System: Created an AI-based biometric system in Python and MATLAB for iris segmentation and secure access control.

Languages

English

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