Salman Qadeer

Manage high-profile client portfolios in the transportation and logistics industry, delivering tailored data solutions to enhance operational efficiency. Ensure client-specific solutions are scalable across the platform, enabling upsell opportunities to other clients in the same industry.

• Ensure unique data needs by developing customized solutions that align with the business objectives of multiple clients in the transportation and logistics sector
• Collaborate with the internal team to establish new standards and norms, making the ETL process smoother and more efficient
• Ensure smooth data flow between various systems and applications, addressing and resolving data-related issues promptly

Key Achievements:

• Developed Methodology to generate the actual driven route of a transportation tour using truck logs, including actual drive time and driven kilometers. This solution enabled a customer to calculate actual costs per consignment and identify potentially expensive clients to avoid bankruptcy. It was also pitched and successfully upsold to other customers
• Developed and applied logic to incorporate planned or target figures into the model, enabling comparison of business performance across all domain customers. It helped in structured comparison framework for actual vs. target data, enabling companies to identify trends, proactively adjust strategies, and optimize resource allocation for improved efficiency
• Optimized ETL and data loading processes by implementing incremental data processing and efficiently handling purged records. These enhancements reduced runtime, minimized server load, and enabled seamless integration of additional daily processes, resulting in a 45% increase in data processing efficiency.

Joined as a founding member, leading the design and implementation of a cloud-based Data Warehouse (DWH) on Google Cloud Platform (GCP). Developed a scalable data architecture enabling advanced analytics and real-time reporting. Collaborated with leadership and cross-functional teams to align data infrastructure with long-term business growth.

• Led the design and implementation of a cloud-based Data Warehouse (DWH) on GCP, utilizing tools like BigQuery, Cloud Storage, Cloud Functions, and Cloud Scheduler for efficient data ingestion and Real-Time Data Processing
• Built the entire data infrastructure from scratch, establishing a strong foundation for company's data needs and supporting the startup's rapid growth
• Collaborated , proposed and rollout various solutions to address gaps in daily processes to ensure the real-time reporting, detailed analysis, and data-driven decision-making for stakeholders from the Operation, Marketing and Commercial teams.
• Managed data integration from various operational systems and third-party services, centralizing data for a 360-degree view of the business

Key Achievements:

• Enabled first-ever Google Cloud Platform-based data warehouse for company to enhance visibility of key business data points. Launching the data warehouse on day one of startup launch provided instant business visibility, enabling top management to make data-driven decisions from the start. This fostered stakeholder engagement, operational efficiency, and strategic agility, ensuring rapid scalability and a strong data-driven foundation for sustained growth.
• Established a live dashboard for business heads to monitor hourly orders and project the run rate for each hour, enabling quick strategy adjustments. This empowered management and marketing teams with real-time insights into deal performance, allowing them to analyze trends and make rapid adjustments. This agility led to significantly improved deal performance, optimizing revenue potential and ensuring data-driven decision-making for sustained business growth.
• Implemented a free alert system (whatsapp message) for the operations team to manage orders from key customers, later expanding its use for various types of alerts. This enabled real-time critical notifications, allowing the business to quickly respond to potential fraud orders, prolonged store closures, and high-priority investor or urgent orders. This significantly improved operational efficiency and customer satisfaction, ensuring swift decision-making and seamless business continuity.
• Established processes and visibility for the application development team to monitor gaps and assess data quality for modules or applications under development. This initiative enabled the application development team to proactively identify and resolve gaps and anomalies during development, leading to faster application releases with fewer iterations for bug fixes. As a result, it enhanced development efficiency, reduced time-to-market, and ensured higher application quality.

Promoted to Big Data Consultant for strong performance, leading data infrastructure optimization within the Cloudera ecosystem. Oversaw SSIS-based ETL pipeline development, ensuring data readiness for critical reporting and predictive banking applications.

• Ensured high-quality, accurate data was available to data scientists, enabling them to build and deploy small-scale banking applications (e.g., fraud detection, credit scoring, and customer insights)
• Led the integration of data from various sources and banking verticals into Datalake, ensuring that the data met the needs of both business intelligence and application development teams
• Led Data Governance & Compliance initiatives, ensuring compliance with data security, privacy regulations, and best practices in data management
• Led and mentored 9 junior team members, providing guidance on best practices, code reviews, and professional development

As an Associate Data Engineer deployed at HBL, Pakistan's Leading Bank. I gained valuable experience working with the Cloudera ecosystem and further developed my expertise in designing and Data Pipeline Optimization. I worked on deploying SSIS-based ETL solutions into Datalake to support reporting processes and business intelligence initiatives, including Power BI dashboards.

• Designed, developed, and optimized SSIS-based ETL using the Cloudera ecosystem, handling large volumes of structured or unstructured data and transform data for reporting purposes
• Troubleshot and resolved technical issues in Data Pipeline Automation and Reporting systems, ensuring smooth Data Delivery

As an Associate Data Engineer for offshore client in South Africa Vodafone. I was responsible for supporting and optimizing data processing workflows, collaborating with cross-functional teams to ensure the efficient and effective delivery of data solutions. My primary focus was on improving existing processes and enhancing the performance of data systems. Optimized and streamlined data pipelines and processes, improving overall system performance and efficiency.

• Conducted performance tuning and troubleshooting to resolve issues related to data processing
• Assisted in the implementation and maintenance of Teradata-based solutions, ensuring data integrity and accessibility