Trissaan A. Shanmugasundaram

I don't just
analyse data.
I build systems
that act on it.

MS Data Science · AWS Certified Data Engineer · 2+ years building production data systems for Mondelez, Nestlé, L'Oréal, and Asahi.

Melbourne, Australia · Open to Work · Full work rights (485 visa, valid Feb 2028)

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Data → Insight → Action

SQL pipelines. Python automation. LLM-powered agents. Power BI dashboards. I build the full stack from raw data to business decisions.

Experience

Data Scientist & Analytics Engineer

Packcentre Marketing Services

Apr 2024 – Mar 2026

15,000+ daily records · SQL/Python pipelines · Power BI dashboards · Enterprise clients (~$2M Mondelez, Nestlé, L’Oréal)

Project Engineer – Data & Automation

Wipro

May 2022 – Feb 2023

Enterprise data migration to AWS · SQL extraction & validation · Dataset reconciliation

Credentials

MS Data Science – Deakin University

BE Electronics – Anna University

AWS Certified Data Engineer

Core Stack

PythonSQLPySparkPower BIAWSFastAPIPostgreSQLLLM APIsDatabricks

Featured Project

I built an AI that applies
to jobs for me.

Full-stack platform: Playwright scrapes Seek listings, GPT tailors my resume & cover letter per job, then tracks every application in a live dashboard. Backend on FastAPI + MongoDB, frontend on Next.js, auth via AWS Cognito.

Background schedulers continuously monitor new listings matching my criteria. No manual applications — the system handles end-to-end.

Step 1

Seek

Job Board Scraping

Step 2

GPT

Resume & Cover Letter Tailoring

Step 3

Cognito

JWT Auth + User Accounts

Step 4

Live

Progress Dashboard

PythonFastAPIPlaywrightOpenAI APINext.jsTypeScriptMongoDBAWS Cognito
View Full Case Study

Packcentre Marketing Services · Apr 2024 – Mar 2026

From 15,000+ records
to real decisions.

Owned the full lifecycle of reporting systems — from schema design through deployment. Partnered with operations, finance, and C-suite to translate requirements into data products.

0+ Daily Records

SQL + Python pipelines with automated validation gates processing transactional data for Mondelez (~$2M), Nestlé, L’Oréal, and Asahi.

Power BI Dashboards

DAX-based KPI measures across financial, logistics, and client performance. Used by operations, finance, and C-suite for decision-making.

Manual → Automated

Replaced Excel-based workflows with Python + SQL automation and Power Automate distribution, eliminating manual handoffs.

Data Quality Gates

Anomaly detection, data drift monitoring, and systematic reconciliation workflows catching errors before they reach downstream systems.

Not just dashboards.
Systems.

End-to-end data infrastructure, from ingestion to insight.

Ingest

PostgreSQL

Transform

Python + PySpark

Orchestrate

Airflow / DAGs

Visualize

Power BI

Automate

AI / LLM

Thesis
01 / 01

Dashboardsdon’t matter.Decisions do.

Every pipeline I ship exists to shorten the distance between a number and an action. Visualisation is the garnish — the work is upstream.

Let's build something
that actually works.

Looking for roles in data engineering, AI systems, and analytics. Melbourne-based, open to relocation, full Australian work rights.

© 2026 Trissaan A Shanmugasundaram