Affsar User

I’m a Senior Data Engineer with 9+ years building scalable, cloud-native data platforms across AWS, Azure, and GCP. I specialize in ETL/ELT pipelines, real-time streaming, data observability, and modern warehouse architectures using Spark, Kafka, Snowflake, and Databricks.

At NiCE, I designed an enterprise-wide data observability framework across 100+ pipelines using Snowflake, dbt, and Airflow to improve transparency and reliability. I built a large-scale data diffing and validation system to compare prod vs staging datasets, achieving 99.8% data accuracy and release confidence, while processing 5B+ records per day with sub-10-minute latency. I reduced data incidents by 40% by implementing schema drift detection, anomaly monitoring, and failure alerts, and I embedded automated data quality checks directly into CI/CD pipelines.

Previously at Slickdeals, I built scalable Spark pipelines for data validation, transformation, and enrichment that power recommendation systems, analytics, fraud detection, and real-time personalization. I expanded observability and data lineage tracking across Snowflake and Airflow workflows, implemented column-level lineage to prevent downstream breakages, and improved Snowflake performance through query optimization, clustering, and warehouse tuning.

Earlier at Foley, I improved ETL pipelines for compliance, risk, and safety datasets using Hadoop and SQL, and built enterprise data warehouse models for Tableau and Power BI dashboards. I also pushed measurable gains in SLA and data accuracy, and I continue to bring a DataOps mindset—governance, CI/CD, and reliable delivery—to every platform I build.