Akhil Bhimana

Built and maintained documentation for cloud infrastructure deployments to standardize operations and improve engineering onboarding. Designed scalable ETL architectures that increased processing speed and improved reliability for analytics teams. Implemented HIPAA-aligned healthcare data pipelines using Azure Data Factory, Azure Databricks, and SQL, including privacy controls for patient-level reporting. Improved collaboration practices and orchestrated ML/prompt-related workflows to enhance delivery efficiency across production environments.

Collaborated with product and business stakeholders to define data products, improving data accessibility and engagement. Improved observability for risk-modeling systems to enable proactive incident response and strengthen operational resilience. Developed AI-native features using TypeScript while refactoring and testing to reduce technical debt. Built AWS ingestion and transformation pipelines for financial datasets, using Redshift and Lambda alongside governed SQL models and security controls.

Integrated Prefect to enhance data orchestration and reduce processing errors across distributed pipelines. Streamlined internal frameworks and data tooling to shorten development cycles and increase team productivity. Built backend solutions enabling large-scale ETL throughput with high availability and fault tolerance, and improved quality through comprehensive testing. Modeled BigQuery datasets and semantic layers and supported analytics delivery using Tableau and Power BI.