Daniel Evans

Bank of America – Data Engineer

• Modernised data pipelines: Migrated numerous SSIS/SQL workflows to Python/Pandas with AutoSys scheduling and Kafka logging, transforming multi-stage legacy processes into modular, maintainable scripts and significantly reducing operational overhead.
• Built an internal ETL framework: Designed Python class templates to standardise each stage of the ETL process, enabling new pipelines to be developed rapidly and consistently.
• Database stewardship: Administered and optimised 200+ SQL views and stored procedures across MS SQL Server and PostgreSQL; led data migrations between platforms to improve performance and reliability.
• Advanced data visualisation: Designed and maintained 20+ Tableau dashboards for enterprise vulnerability tracking; applied UI/UX best practices to improve stakeholder engagement.
• Full-stack tool development: Delivered a Django-based internal application with a custom JavaScript/Tailwind front-end, using Kafka as a message queue for emails, downloads and monitoring. Deployed on the bank’s private cloud with Apache HTTP Server, including a server-maintenance scheduling tool and custom pipeline monitoring.
• End-to-end delivery: Managed full project lifecycle from planning and development to testing and deployment using Git, Bitbucket and Jira, working directly with stakeholders to capture requirements and present solutions.

Tesco - Customer Assistant and Shift Leader

• Worked part-time while studying full-time. Trained and promoted to shift leader to cover schedules, demonstrating reliability, adaptability and a proactive approach to learning.
• Delivered customer service and store operations during busy periods.
• Trained as shift leader and supervised daily tasks, staff rotas and opening/closing procedures when required.
• Developed leadership, time-management and communication skills while balancing work with university studies.

Option Trade Analysis Tool

• Designed and built a high-performance stock market screening platform featuring a full end-to-end data pipeline, analytics dashboard, and cloud-native deployment.
• Real-time data ingestion: Architected and implemented a Kafka-based streaming pipeline ingesting the full flow of U.S. stock-option trades in real time, transforming and persisting data into an S3-backed data lake for scalable storage and analytics.
• API and frontend delivery: Developed a robust REST API with FastAPI to expose processed data to client applications; built a responsive, real-time dashboard in Next.js/React for visualisation and analytics.
• Cloud deployment & observability: Containerised the entire stack and deployed to AWS ECS with Fargate using Terraform for infrastructure-as-code. Implemented comprehensive monitoring and alerting using Prometheus and Grafana.
• Technology depth: Demonstrated expertise in real-time data pipelines, Python, JavaScript/TypeScript, React, and cloud infrastructure, with hands-on orchestration and automation across the full stack.

Home “Cloud” Network

• Built a personal virtual environment on Proxmox hosting multiple VMs (PostgreSQL database, Plex server, custom DNS), configuring and managing Linux servers and network settings to deepen expertise in virtualisation, system administration and infrastructure setup.

University of Leicester - MPhys Physics with Space Science

• Predicting star classification using Gaussian Processes – Modelled time-series data with Python and R, applying Gaussian processes and Fourier transforms to develop predictive scientific models on the classification of stars.
• Dynamics of Circumbinary Planets – Simulated three-body orbital dynamics on a supercomputer using C and batch processing to identify stable orbits.

King Edward VI Sixth Form College