// 02 • CAREER TIMELINE & ARCHITECTURE

Building digital products & enterprise scale.

Professional Journey6+ Years • Enterprise Strategy & Engineering
SCROLL TO EXPLORE ARCHIVE
PILLAR 01

Platform Engineering

01
♦80% Ingestion Time Saved
  • Built robust Databricks pipelines using APIs to automate data integration from various applications to Apptio.
  • Led the automation of financial data ingestion from SAP, GCP, and Azure into IBM Apptio, saving 80% resource time.
DatabricksIBM ApptioSAPGCPAzure API
PILLAR 02

Strategy & FinOps

02
♦~$100M/mo Governed · $5M Saved
  • Managed ~$100M monthly IT spend, ensuring seamless IT Financial Management.
  • Established cost transparency across 64 applications (~$100M/month), enabling strategic resource allocation.
  • Developed end-to-end persona-based financial reports driving $5M in cost savings for key CIO projects.
TBM FrameworkFinOps64 AppsUnit Economics
PILLAR 03

Gen AI & Innovation

03
♦GenAI Copilot PoC · 80% Faster QA
  • Developed a Gen AI (Copilot) Proof of Concept that automated platform evaluations, reducing technical debt.
  • Implemented comprehensive data quality testing frameworks achieving an 80% reduction in manual testing time.
Copilot AIAzure OpenAIData Quality TestingPython
PILLAR 04

Data Operations

04
♦66% Runtime Reduction
  • Designed and optimized ELT pipelines to transform data across geographies, reducing transformation time by 66%.
Global ELTCross-Geo SyncData Pipelines
PILLAR 01

Data Engineering

01
♦$20M Preserved · 66% Faster ETL
  • Created ETL pipelines for Pharmacovigilance documents, saving 66% processing time and 50% operational costs.
  • Mined and wrangled massive medical insurance datasets in AWS for Value-Based Contracts, saving clients $20 Million.
  • Automated semi-structured file conversion to enhance ETL application compatibility.
AWS RedshiftS3 LakehousePharmacovigilance
PILLAR 02

Cloud Architecture

02
♦50% Infra Cost Cut · 3x Throughput
  • Assisted in creating a Data Science Software Architecture that reduced cloud infra costs by 50% and improved revenue by 3x.
  • Analyzed AWS Lakehouse, Glue, and Blueprints vs self-developed EC2 pipelines for Life Sciences industry insights.
AWS GlueLakehouseEC2 Microservices
PILLAR 03

Development

03
♦80% Dev Velocity Boost
  • Constructed a reusable Python library for Pharmacovigilance documents, cutting future development time by 80%.
  • Created microservices dedicated to Exploratory Data Analysis (EDA) and causal inference.
Python CoreEDA ServicesReusable Framework
PILLAR 04

Automation

04
♦75% Test Time Reduction
  • Developed an automatic testing web application that reduced testing and report generation time by 75%.
Web EngineAutomated QACI/CD
// 03 • CAPABILITY MATRIX

Technical Arsenal

01

Languages & Software

PythonJavascriptMatillionIBM Apptio
02

Frameworks & Libraries

FastAPIFlaskPandasNumpyMatplotlibPlotlyVueNuxt
03

Cloud Services

S3RedshiftRDSEC2Google Cloud FunctionsAWS LambdaAWS Lakehouse
04

SDLC & Tools

AgileDevOpsGitDockerCI/CDJira