Umer Sheikh

I am a senior data engineer with five years of experience designing and delivering scalable data pipelines, real-time streaming systems, and cloud-based analytics platforms. I specialize in building production-ready ETL/ELT workflows and enabling analytics and ML teams with high-quality datasets.

My recent work includes designing event-driven workflows and real-time ingestion frameworks using Spark, Kafka, Airflow, and AWS services. I focus on reliability, observability, and cost optimization through monitoring, partitioning, and efficient data modeling.

I have implemented cloud-native pipelines across AWS, GCP, and Azure, worked with Snowflake, Delta Lake, and BigQuery, and supported ML feature engineering and MLOps practices. I automate data validation and monitoring to maintain pipeline stability and data quality.

I bring strong hands-on experience with distributed processing, infrastructure-as-code, and observability tooling, and I am committed to building robust data platforms that scale and reduce operational costs.