Technical and Professional Experience

Cloud Financial Operations Manager

Certified FinOps Practitioner: Understand FinOps practices and how cloud operations enhance business value
Collaborate with AWS, GCP, and Azure cloud business partners and project managers to establish a centralized FinOps governance, review monthly cloud expenses and forecasts, and identify opportunities for savings and efficiencies in upcoming efforts
Reduced anomalous cloud spend by $1M in 2024 through strategic cost analysis and process improvements
Developed ETL (Extract, Transform, Load) with Python to ingest, format, and load cloud financial data into a database
Automated cloud financial reporting and visualization for stakeholders to track monthly cloud utilization
Designed a SQL database and Python ETL to ingest, format, and process cloud financial data for monitoring and modeling

Designed, documented, and implemented all software/database architecture, ETL, data processing tools, and visualizations
Reduced a monthly 20+ hour process to an instantaneous process by automating Configuration Management metric reporting with a Python ETL and a relational MySQL relational database hosted on Amazon Web Services (AWS)
Collaborated with data teams to develop automated data reporting APIs from data owning servers to recipient S3 buckets in the Configuration Management AWS instance, thereby automating their previously manual monthly reporting procedures
Developed interactive Tableau dashboards to facilitate data exploration through publicly accessible team SharePoints

Designed and implemented a scalable relational database architecture to securely store 20 years of legacy data, accommodate future data entries, and implement data governance strategies to retain data security and integrity
Automated an ETL pipeline in Python to drastically reduce procedural timelines and program expenses
Streamlined data processing algorithms to automate crucial data metric reports and visualizations, drastically reducing a historically 8-hour process per experiment to an instantaneous automated workflow
Improved the data analysis user experience by creating a library of modular graphical user interface tools with TKinter that facilitate interactive data exploration, cleaning, and visualization for non-technical users
Automated mechanical systems' data processing and optimization procedures to identify opportunities for improvement
Implemented statistics and computer vision practices to develop robust data characterization algorithms

Designed an innovative DC motor control system with a robust data characterization algorithm to automate a historically manual procedure, reducing a tuning procedure from up to 8 hours of manual labor to an automated 30 seconds
Overhauled existing technology, electronics, and relevant test fixtures to drastically improve system performance, yielding significant timeline savings and 80% cost savings in electrical hardware per fixture, per testbed
Standardized testing fixtures and procedures for secure data acquisition protocol for analyses
Led design reviews comprised of engineers with diverse technical backgrounds and varying proficiencies in mechanics, electronics, and software to assess design performance and utility
Oversaw various teams' data acquisition efforts while adhering to firm program schedules and budgets

Microsoft SQL Server | PostgreSQL | MySQL

Entity Relationship Diagrams (ERD) | Extract, Transform, Load (ETL/ELT) | Data Warehouse/Lake | Data Exploration | Data Visualizations