Technical Engineering and Data Architecture Professional experience spans over 10 years in the design and optimization of large-scale, cloud-native data pipelines and high-reliability software solutions. Technical proficiency includes architecting multi-terabyte-per-day telemetry ingestion systems using Python, Java, C++, and SQL. Core expertise involves using Spark, PySpark, and Databricks for end-to-end ETL and ELT workloads, alongside Azure cloud services such as Synapse Analytics, Event Hubs, and Cosmos DB. Advanced systems work includes deploying microservices on Kubernetes and establishing CI/CD frameworks with GitHub Actions and PyTest that increased test coverage from 0 to over 80 percent. Automotive Systems and Quality Engineering A significant portion of this technical career...