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Schedule Interview NowMy name is Waleed A. and I have over 9 years of experience in the tech industry. I specialize in the following technologies: Tableau, SQL, Business Intelligence, Big Data, Apache Hive, etc.. I hold a degree in Bachelor of Engineering (B.Eng.). Some of the notable projects I’ve worked on include: Streamlined ETL Processes and Cut Costs for Marketing Firm, ETL Development and Data Integration for Real Estate Finance, Improved Data Management and Reporting for a Tech Company, Centralized Job Data Platform for Staffing and Recruiting, Optimized Data Integration and Analytics for Health and Fitness, etc.. I am based in Lahore, Pakistan. I've successfully completed 14 projects while developing at Softaims.
I am a business-driven professional; my technical decisions are consistently guided by the principle of maximizing business value and achieving measurable ROI for the client. I view technical expertise as a tool for creating competitive advantages and solving commercial problems, not just as a technical exercise.
I actively participate in defining key performance indicators (KPIs) and ensuring that the features I build directly contribute to improving those metrics. My commitment to Softaims is to deliver solutions that are not only technically excellent but also strategically impactful.
I maintain a strong focus on the end-goal: delivering a product that solves a genuine market need. I am committed to a development cycle that is fast, focused, and aligned with the ultimate success of the client's business.
Main technologies
9 years
8 Years
4 Years
5 Years
Potentially possible
Systems Limited
Pain Points: The company struggled with slow ETL processing, high resource costs, and time-consuming manual data tasks, limiting scalability and increasing operational expenses. Solution: I re-engineered ETL workflows on GCP, deploying Docker on Cloud Run for improved scalability and BigQuery partitioning to reduce storage by 500GB. Custom Python scripts automated 5,000+ daily entries, while Google App Script eliminated manual tasks, greatly boosting team efficiency and Productivity. Results (ROI): 50% increase in data handling 30% reduction in storage costs 20 hours freed up weekly
Pain Points: A real estate firm struggled with managing complex data from multiple sources, limiting informed decision-making. Solution: Built a scalable data system on Google Cloud Platform, automating the ETL pipeline to integrate over 2 million entries from Salesforce and Google Sheets into BigQuery. Python scripts enhanced data accuracy and efficiency, while Looker Studio dashboards provided real-time insights, giving the client easy access to essential data for improved decisions. Results (ROI): - 50 Hours Saved Weekly - Fewer Errors - Lower Processing Costs
Pain Points: A tech company faced inefficiencies from scattered data systems, delaying reporting and decision-making. Solution: I created a centralized data system on Google Cloud Platform, integrating multiple sources into BigQuery. SQL transformations improved data query speeds, and 10+ Looker Studio dashboards offered real-time access to critical metrics. Advanced Looker analytics enabled detailed performance tracking for faster, data-driven decisions. Results (ROI): 60% Faster Processing 30 Hours Saved Weekly 40% Increase in Operational Efficiency
Pain Points: The client’s job listings were scattered across sources, making tracking difficult and creating inefficiencies. Solution: I built a centralized platform on Google Cloud Platform (GCP). Google Cloud Storage consolidated 50,000+ listings, the SERP API ensured up-to-date content, Cloud Functions automated updates, and BigQuery with Looker Studio provided fast queries and dashboards. Results (ROI): 50K+ job listings consolidated efficiently 15 hours saved per week 30% improvement in service delivery
Pain Points: Data variability from wearables created processing challenges, and the company needed a scalable system for Apple Watch data and growing datasets. Solution: We created a flexible Google Cloud setup, integrating Firebase with BigQuery to manage millions of daily data points and 200GB+ in transactions. Python scripts automated data cleaning, while Compute Engine enabled advanced analysis for actionable insights Results (ROI): Millions of data points processed daily 40% reduction in manual intervention 35% improvement in analytics efficiency
Bachelor of Engineering (B.Eng.) in Computer science
2013-01-01-2017-01-01