Syeda Yasir

I am a senior data engineer with over a decade of experience designing scalable, cloud-native data infrastructures and machine learning pipelines across AWS, Azure, GCP, and Databricks. I focus on reliability, automation, and delivering measurable business value through batch and streaming processing, orchestration, and MLOps.

I've architected and deployed production-grade pipelines using Apache Spark, Delta Lake, Databricks, Airflow, dbt, Kafka, and cloud-native services, improving throughput and reducing latency and costs. I have delivered ML/LLM workflows using MLflow, LangChain, vector databases, and monitoring stacks like Prometheus and Grafana, and I build CI/CD and infrastructure-as-code to ensure reproducible, observable deployments.

I take a pragmatic, metrics-driven approach to data quality, governance, and operational resilience, integrating Great Expectations, Unity Catalog, RBAC, and observability to minimize incidents and support business-facing analytics and AI products.