Ahmad Ali

I’m an AWS-certified senior data engineer with 11 years of experience designing, building, and optimizing end-to-end data platforms and pipelines across Python ecosystems, cloud services, and streaming + batch workflows. I focus on production-grade ETL/ELT, analytical data models, and secure, scalable ingestion that meets real compliance and performance needs.

At Medtronic, I drove HIPAA-compliant, cloud-enabled data engineering for ambulatory patient monitoring—building secure ingestion and transformation pipelines, automating HL7 parsing/normalization, and deploying event-driven microservices on Amazon EKS with Docker. I also delivered near real-time clinical analytics with Snowflake (Bronze/Silver/Gold medallion architecture using Snowpipe, Stages, and dbt), enforced governance with row-level security and dynamic masking, and modernized Kafka workloads by migrating to Amazon Kinesis while preserving exactly-once processing semantics.

I love pushing beyond “just pipelines”: I integrate AI-augmented capabilities like RAG (LangChain/LlamaIndex, OpenAI embeddings, pgvector), MCP-based agent connectivity to live operational data, and TensorFlow inference served on Amazon SageMaker endpoints with a FastAPI orchestration layer. I’m committed to mentoring engineers and building teams that value data quality, automation, and measurable AI-driven improvements.