Toyosi Taiwo

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Senior Data Engineer @ AutoComply
I like to learn new things, stay fit, and play chess

Projects

EPL match predictor

Aug, 2020
Technologies Used:   R, Machine Learning,
  • Developed machine learning models to predict match outcomes using betting odds data, rolling average team statistics, team reputation and expected goals with up to 55% prediction accuracy

footsteps

May, 2012
Technologies Used:   Android, Java, GPS, SQL.
  • Android app that displays real-time location of friends, with small social network capabilities. Designed the location and mapping algorithm using GPS signals and network towers to optimize performance.

mosfet fabrication and characterization

May, 2015
Technologies Used:   SEM, Silicon, mosFET, Photolithography, Ion Implantation, Diffuson.
  • fabrication and characterization of devices on n-type and p-type wafers.

deblurring and denoising

July, 2011
Technologies Used:   MATLAB
  • Developed MATLAB scripts to deblur and denoise images using matrix manipulation techniques Singular Value Decomposition (SVD), Fourier transformsand filtered deconvolution.

δ doping concentration

May, 2016
Technologies Used:   MEDICI, HEMT, FET.
  • Effect of δ doping concentration and location on Al0.2Ga0.8As/In0.85Ga0.15As HEMT performance

Work History


RPI

AutoComply

June 2026–Present
Senior Data Engineer
Technologies Used:  Google Cloud Platform, Terraform
  • Automated deployment of Google Cloud Platform data pipelines and cloud functions using Terraform, improving release velocity and platform reliability for downstream consumers.

RPI

Microsoft

November 2020–October 2025
Software Engineer II
Technologies Used:  Python, SQL, C#, TypeScript, Azure Databricks, Azure Stream Analytics, Cosmos DB, Azure OpenAI, React, SQL Server, Azure App Service, Azure Data Factory, Azure Data Explorer, ClickHouse.
  • Built and maintained ETL/ELT pipelines with Azure Databricks consumed by 50+ downstream teams, ensuring reliable, well-modeled data for Microsoft Copilot adoption reporting.

  • Designed and operated a high-throughput streaming data platform using Azure Stream Analytics and CosmosDB to ingest application events from Microsoft devices and web surfaces into analytics-ready datasets.

  • Led a team of 4 engineers building a multi-agent, LLM-powered reporting system using Azure OpenAI, translating complex operational data into clear service health reports for leadership overseeing 200+ engineers.

  • Built and owned a full-stack metadata management web app and API using React, SQL Server, and Azure App Service, standardizing metadata for thousands of ad campaigns and ensuring data accuracy across Microsoft and partner surfaces.

  • Built a self-service pipeline creation tool that embedded authentication, schema validation, and compliance checks for data analysts and scientists, saving hundreds of engineering hours and improving data integrity.

  • Designed data quality, monitoring, and observability systems using Azure Data Explorer and Blob Storage, cutting incident investigation time from multiple days to under 3 hours.

  • Partnered with product, analytics, and leadership stakeholders to drive adoption of new platforms like ClickHouse across the organization.

  • Owned hundreds of Azure Data Factory pipelines supporting consumer attribution modeling, deployed through CI/CD pipelines to ensure reliable, repeatable releases.


RPI

GLOBALFOUNDRIES

September 2016–December 2017
Software Engineer / Device Engineer
Technologies Used:  R (data.table, ggplot2, dplyr, shiny, e1071, carat, parallel), Python, Java, UNIX Shell, Git/SVN, Cadence, FinFET.
  • Developed web app with R (Shiny), SQL and python for dynamic analysis, statistical modelling, and visualization of millions of rows of 7nm finFET experimental data - Reduced report generation runtime from hours to minutes.

  • Used bash scripting to automate data collection and preparation, and Git to work with team members.

  • Designed, verified, and benchmarked foundry ready 7nm series and parallel stacked finFETs using Cadence/li>


RPI

Rensselaer Polytechnic Institute

August 2014–May 2016
Head Teaching Assistant
Technologies Used:  Embedded C, c8051 Microcontroller
  • Head T.A for Laboratory Introduction to Embedded Control (LITEC) and Electric Circuits courses.

  • Duties involved teaching students, organizing the rest of the TAs for lab sessions, exam proctoring, and grading coursework.


RPI

Fisk University

September 2009–May 2011
Student Researcher - Material Science and Applications Group
Technologies Used:  Semiconductor, Cadence, E-beam Evaporator, Radiation Detection, IR spectroscopy
  • Assisted with the fabrication of semiconductor crystals like CZT and SrI2 as small as 0.5 mm thickness.

  • Performed tasks that included photolithography, mechanical etching, and radiation detection measurements