ATEEQ UR REHMAN

MAKING DATA USEFUL

Snowflake Cost & Performance Optimization Specialist

Helping companies reduce Snowflake compute costs by 20–40% while improving warehouse performance, query efficiency, and workload architecture.

I specialize in Snowflake architecture design, warehouse right sizing, query optimization, clustering strategy, workload isolation, and Cortex AI integration. With 10+ years in data engineering and deep Snowflake expertise, I help organizations eliminate waste, improve performance, and build scalable, cost-efficient cloud data platforms.

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About Me

I’m Ateeq ur Rehman, a Snowflake Cost & Performance Optimization Specialist with over 10 years of experience in data engineering and analytics architecture. I help organizations reduce Snowflake compute costs, improve warehouse performance, and design scalable, efficient cloud data platforms.

My work focuses on identifying architectural inefficiencies, optimizing workloads, and implementing best practices that drive measurable performance gains and cost savings. Over the years, I’ve worked across diverse data ecosystems from traditional relational systems to modern cloud-native platforms. This background enables me to approach Snowflake environments with both deep technical precision and strategic architectural insight.

My Snowflake Expertise

Warehouse right-sizing and workload isolation.
Query performance tuning and execution analysis.
Clustering and micro-partition optimization.
Cost visibility modeling and usage governance.
Architecture design for scalable analytics.
Cortex AI integration for intelligent data workflows.

I focus on building secure, high-performance, and cost-efficient Snowflake ecosystems that support enterprise analytics and AI-driven decision-making.

Snowflake Cost Optimization & Performance Improvement

Optimized Snowflake workloads and data models to reduce operational costs while improving query performance and overall platform efficiency.

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Enterprise Data Warehouse on Snowflake

Designed and implemented a scalable enterprise data warehouse to support analytics and reporting across multiple business domains.

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My Data Engineering Projects

Enterprise Data Warehouse in Snowflake

Designed and implemented a scalable enterprise data warehouse using Snowflake, enabling unified analytics and real-time insights across multiple business data sources.

This project demonstrates a modern data pipeline for e-commerce analytics, designed to integrate, process, and visualize large volumes of transactional and behavioral data. Data from operational databases is ingested using Hevo, while API and log data are streamed through Apache Kafka and Apache Flume for real-time capture. All raw data is centralized and transformed within Snowflake using dbt and Airflow to build curated analytical layers. Finally, Power BI dashboards deliver rich insights into customer behavior, sales performance, and operational trends — enabling data-driven decision-making across the business.