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Senior Data Engineer | Snowflake | Spark | Kafka | dbt

Building Scalable Data Platforms for Business Impact

I design and build scalable, cloud-native data platforms that help organizations make reliable, data-driven decisions. With deep experience in data engineering and analytics architecture, I transform raw data into high-quality, analytics-ready datasets that drive operational efficiency, growth, and measurable business impact.

  About Me

Ateeq ur Rehman, a data engineer and consultant with more than a decade of experience in the data industry, focused on data engineering and architecture.

I specialize in designing and implementing data solutions across modern cloud platforms using advanced ETL frameworks and data integration tools. I’m deeply focused on transforming raw, unstructured, or disconnected data into clean, actionable insights that enable organizations to make smarter and faster business decisions.

Having worked across diverse data environments from relational databases to modern data lakes and pipelines, I bring a balanced mix of hands-on technical expertise and strategic thinking.

My Big Data & Cloud Expertise

As a Snowflake-certified Senior Data Engineer and Big Data expert, I architect and optimize scalable, multi-cloud data platforms across AWS, Azure, and GCP.

My expertise spans Spark, Hadoop, Kafka, Airflow, and dbt, along with containerization (Docker, Kubernetes), CI/CD automation (Terraform, Jenkins, GitLab), and strong data governance practices (IAM, RBAC).

focus on building secure, cost-efficient, and high-performance data ecosystems for enterprise analytics and AI-driven insights.

Selected Case Studies

Snowflake Cost Optimization & Performance Improvement

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

Enterprise Data Warehouse on Snowflake

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

My Data Engineering Projects

Enterprise Data Warehouse in Snowflake

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

E-commerce Analytics Platform on Snowflake

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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.