Mathews Philip Venattu - MPV
SOLUTIONS ENGINEER / FORWARD DEPLOYED ENGINEER / DATA ANALYST /
Mathews Philip Venattu
Hi,I am
Mathews Philip Venattu

Solutions Engineer / Forward Deployed Engineer /
Data Science & Analytics

Philadelphia, PA•Open to Roles

Over 5+ years of enterprise experience

MS in Data Science & Analytics (Honors)

Contact Me
Professional Profile & Ethos

Hi there — I'm Mathews.

If you're looking for someone who can sit across from an enterprise client, speak the language of business stakeholders, and then turn around and write the Python, DAX, or serverless cloud architecture to make it real — that's exactly what I do.

Over the past 5+ years, I’ve operated at the intersection of Solutions Engineering, Forward Deployed Execution, and Data Analytics. Serving as the dedicated Subject Matter Expert (SME) for AMCS Field Services API endpoints, I partnered directly with client engineers from a Fortune 10 global energy enterprise—guiding their integration architecture, helping them select the right endpoints, and ensuring their systems connected seamlessly.

On the data and infrastructure front, I’ve engineered event-driven pipelines on AWS (Lambda, SQS, S3) ingesting live telemetry from over 800 remote operational assets daily, and designed interactive Power BI dashboards with advanced DAX to turn complex operational data into clear, actionable executive decisions.

What drives me every day is velocity and practical problem-solving. Through Omnity Labs, a personal initiative alongside like-minded builders, I focus on rapid prototyping—taking tangible problems and building working, production-grade solutions in days using modern AI developer workflows (Claude, Google Antigravity, and serverless stacks).

View My Technical Skills
Philadelphia, PA (US Green Card)
Timeline & Milestones

Software Engineer

Mermer Technologies India Pvt Ltd
Aug 2019 – Aug 2020
Republic of India
  • Led frontend engineering using TypeScript and the Angular framework, designing modular user interfaces and integrating RESTful endpoints.
  • Promoted to Team Lead to facilitate sprint planning, manage task breakdowns, and clarify technical requirements for engineers.
  • Analyzed ambiguous legacy codebases to identify performance bottlenecks and execute sound architectural trade-offs.

Frontend Engineer / Solutions Consultant

AMCS Group
Sep 2021 – Aug 2024
Republic of Ireland
  • Led client workshops, product demos, and technical configuration sessions to deploy enterprise customer portals and integrated payment workflows.
  • Partnered with Product Owners and Solutions Architects during UAT and hyper-care phases, inspecting and resolving database discrepancies in MS SQL Server.
  • Authored comprehensive technical documentation, solution designs, and structured test cases ensuring seamless customer handoffs post-launch.
  • Built automated workflows using Microsoft Power Automate to sync project data across tracking sheets and automate deployment ticket generation.
Concurrent Specialization Tracks

Solutions Engineer / Data Analyst

AMCS Group
Aug 2024 – Present
Philadelphia, PA (Mar 2025 – Present) & Rep. of Ireland (Aug 2024 – Mar 2025)
  • Served as the dedicated API integration specialist for a Fortune 10 global energy enterprise, defining endpoint selection, payload schemas, and authentication models.
  • Architected an event-driven telemetry ingestion pipeline using AWS SQS and AWS Lambda, processing data from 800+ remote operational assets 3x daily within strict API rate limits.
  • Engineered serverless batch-processing engines using chained AWS Lambda functions and S3 to parse and validate high-volume onboarding datasets (up to 20,000 records).
  • Built automated Python ETL workflows using the dlt package and AWS Lambda cron jobs, leveraging AI developer tools to accelerate data pipelines.
  • Engineered interactive Power BI dashboards utilizing advanced DAX and optimized SQL queries to deliver actionable operational insights to enterprise and municipal utility stakeholders.

Co-Founder

Omnity Labs Incomnitylabs.com
Feb 2026 – Present
Philadelphia, PA
  • Co-founded an engineering collective dedicated to solving real-world challenges by building and productizing AI-driven automation workflows for broader market use.
  • Architect rapid full-stack applications using Google Antigravity, Claude, Firebase, and GCP to accelerate the 0-to-1 development cycle and achieve fast shipping velocities.
  • Drive the end-to-end productization of internal proof-of-concepts, transforming targeted rapid prototypes into scalable, accessible applications that resolve everyday user bottlenecks.
Academic Credentials & Research

2020 – 2021

Master of Science in Data Science and Analytics

National University of Ireland, Maynooth

1:1 First Class Honours (US GPA: 4.0)
Academic Focus & Thesis
  • Postgraduate Research: Planetary magnetosphere boundary classification on NASA/ESA Cassini Spacecraft magnetometer data.
  • Core Disciplines: Statistical modeling, machine learning systems, distributed databases & spatial analysis.
Relevant Course Modules
Statistical Machine LearningR for ProgrammingLinear ModelsSpatial Databases (QGIS & PostgreSQL)Statistical Methods for Data Science
Degree 1 of 2
2015 – 2019

Bachelor of Technology in Electrical and Electronics Engineering

APJ Abdul Kalam Technological University

Upper Second Class Honors (2:1)
Activities & Societies
  • Served as the Chairman of Film Club
  • Served as the Technical Head of IEEE Saintgits Student Branch
  • Served as the Treasurer of IEEE Saintgits Students Branch
  • Squad Member of Saintgits Basketball Team
Relevant Course Modules
Distributed Generation and Smart Grids (DERs)Power SystemsThree-Phase Distribution NetworksFoundational Electrical Engineering Principles
Degree 2 of 2
Swipe to explore degrees
Research & Publications
Master's Thesis & DissertationMaynooth University • 2021

Classification of Bow Shock and Magnetopause Boundaries of Saturn

Conducted complex statistical analysis and data exploration on the 2005 NASA/ESA Cassini Spacecraft magnetometer datasets.

  • Applied foundational statistical methods, including Logistic Regression with Maximum Likelihood Estimation, to evaluate predictor significance and eliminate uninformative variables to prevent overfitting.
  • Trained, validated, and optimized Random Forest and Lasso Regression classification models using R, caret, ranger, glmnet, and tidyverse.
  • Evaluated competing models across multiple derived datasets, prioritizing high sensitivity metrics to accurately identify and classify distinct boundary crossing categories.
RStatistical ModelingRandom ForestLasso RegressionLogistic Regression (MLE)caretrangerglmnetCassini Datasets
Publication 1 of 2
Peer-Reviewed PublicationTaylor & Francis / CRC Press

Development of an Inductive Wireless Charging Scheme for Dynamic Charging of Electric Vehicles

Co-authored research chapter in Emerging Technologies for Sustainability exploring inductive power transfer architecture and dynamic EV charging feasibility.

Publication 2 of 2View Publication
Swipe to explore publications
Technical Competencies

Solutions Engineering

  • Technical Discovery & Scoping
  • SOW Authoring & Architectural Trade-offs
  • REST API Scoping & Integration
  • Enterprise Onboarding & UAT
  • Cross-Functional Stakeholder Delivery
Category 1 of 6

Cloud & Backend Architecture

  • AWS (Lambda, SQS, S3, Event-Driven)
  • GCP (Cloud Functions, Serverless)
  • Serverless Batch Processing
  • Webhooks & RESTful Web Services
  • API Rate Limiting & Payload Mapping
Category 2 of 6

AI & Workflow Automation

  • Google Gemini API (Multimodal Extraction)
  • n8n Workflow Automation
  • Local LLM Deployment (Gemma)
  • Prompt Design & Structured Outputs
  • Microsoft Power Automate
Category 3 of 6

Languages & Frameworks

  • Python & R
  • TypeScript & JavaScript
  • SQL (PostgreSQL, MS SQL, MySQL)
  • React & Next.js
  • Flutter (Dart) & Angular
Category 4 of 6

Data Engineering & Reporting

  • PostgreSQL (Neon DB, pgvector)
  • ETL Pipelines (Python dlt package)
  • Power BI & Advanced DAX
  • Firestore & Firebase Studio
  • Data Validation & Schema Mapping
Category 5 of 6

Statistical Modeling & Machine Learning

  • Random Forest & Lasso Regression
  • Logistic Regression & MLE
  • R Ecosystem (caret, ranger, glmnet, tidyverse)
  • Model Sensitivity & Classification Evaluation
  • Exploratory Data Analysis & Feature Selection
Category 6 of 6
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Featured Projects & Implementations

Mobile & AILIVE
Smart Receipt Scanner & Expense Analytics

Your Billbox

Omnity labs Inc • In Production • App Store & Play Store (v1.0.4)

B2C mobile application built with Flutter. Employs serverless GCP Cloud Functions and the Google Gemini API to parse unstructured paper and digital receipt images into validated JSON records in real time, with event-driven sync to Neon DB PostgreSQL.

Multimodal Receipt Extraction & Event-Driven Database Sync
FlutterGoogle Gemini APIGCP Cloud FunctionsPostgreSQL (Neon DB)Antigravity
Project 1 of 5Live Link
Workflow AutomationSAAS IN DEV
Local LLM Cold Email Generation via n8n

AI Outreach Automation Engine

Omnity Labs Inc • Production Pipeline

Automated cold email generation pipeline connecting Google Sheets to an LLM via n8n. Scrapes company websites, prompts the model for context-aware messaging, and writes personalized drafts back to the sheet. Currently being productized into a public web app.

Currently productizing this internal workflow into a public SaaS platform at omnityspace.com, upgrading the core engine to the Gemini API.
n8nGemini APIGemma (Local LLM)Google Sheets APIPrompt Engineering
Project 2 of 5Live Link
Cloud & DataLIVE
Multi-Tenant Data Management Platform

Flock Trail

In Production (v2.0.0)

Enterprise multi-tenant platform comprising an Admin Command Center, Member Web Dashboard, and native Android application built with Next.js, React, Tailwind CSS, and Firestore, featuring automated subscription billing and role-based access control.

Multi-Tenant Architecture with Automated Subscription Workflows
Next.jsReactFirestoreTailwind CSSRBAC AuthAntigravity
Project 3 of 5Live Link
Research & MLRESEARCH
Planetary Shock Wave ML Classification

Saturn Magnetosphere Classifier

Academic Research • NASA/ESA Cassini Mission

Complex statistical modeling and supervised machine learning analysis on 2005 NASA/ESA Cassini Spacecraft magnetometer datasets to classify bow shock and magnetopause boundary crossings using logistic regression MLE, Random Forest, and Lasso.

High-sensitivity planetary boundary detection on NASA/ESA datasets
RcaretRandom ForestLasso RegressionStatistical Modeling
Project 4 of 5
Full Archive
Complete Engineering Portfolio

Explore All Projects & Research

Dive into the complete archive of production applications, enterprise cloud ETL pipelines, local open-source LLM engines, and peer-reviewed research publications.

Includes filtering by stack & category
Architectural breakdowns & metrics
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Archive Card 5 of 5
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Open for Opportunities

Actively looking for Solutions Engineer, Data Analyst, Forward Deployed Engineer and API Integration roles.

mathewsvenattu@gmail.comLinkedIn
Philadelphia, PA•US Permanent Resident (Green Card)•github.com/matty1203