As Engineering Lead, I architected a multi-tenant platform using Kubernetes CRDs and Operators in Java/Quarkus, which cut deployment time by 40%. I also designed a SaaS billing system with Lago, saving 3% in revenue, and led the development of AI-powered RAG features to summarize benefits and claim status, providing crucial time savings for healthcare administrators. My work on automating batch processing for eligibility and claims reduced API costs by 25%.

In this role, I led backend development for a digital healthcare marketing platform using FastAPI, PostgreSQL, and Kubernetes, ensuring a scalable and highly available system. I mentored a team of three engineers, improving our productivity, and worked closely with product and marketing to translate business needs into technical solutions. This work included developing data pipelines that improved marketing campaign ROI by 18%.

As a Data Engineer, I focused on optimizing our big data workflows. I improved existing Spark jobs by fine-tuning queries and cluster configurations, which reduced Azure DBU costs by 20%. I also implemented custom Spark UDFs in Java for critical tasks like data decryption, DICOM image parsing, and converting data from FHIR to HL7 for ingestion into cloud EHRs, while also mentoring junior team members on best practices.

In my first role at the company, I implemented APIs to ingest and process media with FFmpeg for streaming. I also built a better search experience by transcribing media with Google Speech to Text and indexing the content with Elasticsearch.