Data Science Software Engineer II Automation NTH
Architected real-time streaming integration using Azure Functions and Kafka, processing 2+ GB of manufacturing data daily and reducing data availability lag from 4 hours to 2 minutes (98% latency reduction). Optimized Azure Cosmos DB queries and indexing strategies, accelerating report runtimes from 5 minutes to 10 seconds (97% improvement). Engineered ETL pipelines using Python, SQL, and AWS Lambda to ingest manufacturing data into Snowflake, maintaining 99.9%+ pipeline availability through automated monitoring and proactive failure resolution. Designed dimensional data models in MS SQL, MariaDB, and PostgreSQL for centralized OLAP warehouses. Built CI/CD workflows in Azure DevOps reducing deployment failures by 80%. Created internal web tooling using React and Power BI visualizations, reducing time-to-action by 40%. Integrated AI-driven automation using LLM APIs to improve task efficiency by 30%. Collaborated with product managers and BI stakeholders to define data product requirements and establish data governance.