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PRANAV DADI / DATA ENGINEERDUBLIN, CALIFORNIA

Good data.
Real possibilities.

I build pipelines that make messy data useful.
From AI powered ingestion to enterprise data quality,
I care about what happens between source and insight.

Explore my work↓
THE SPACE I WORK INSELECT A STAGE TO EXPLORE

At QuickCruit, I built Python ingestion pipelines across 300+ company career sites.

Selected work (05)

BUILT. VALIDATED. ALWAYS EVOLVING.
01 / QUICKCRUIT.AI2024 — 2025

From scattered jobs
to structured data.

An AI powered ingestion platform that turns unstructured job postings into consistent, searchable records.

PythonVertex AI / GeminiMongoDB
Explore the project +

The challenge

Hundreds of career sites publish job data in different formats. Downstream search needs reliable, consistent fields.

My contribution

Built ingestion and ETL pipelines, integrated Gemini to structure titles, locations, compensation and skills, and added validation, checkpoints and recovery logic.

The result

Processed 100,000+ records with 95%+ structured output accuracy. Reduced filtering time from 48 hours to under 48 minutes and failed AI processing runs by 30%.

Visit QuickCruit ↗
PIPELINE PERFORMANCE / QUICKCRUIT
60×
faster job filtering
Before
48 hours
After
< 48 min
300+ sources100K+ records
STANFORD UNIVERSITY / HR TECHNOLOGY
PeopleSoft→Oracle HCM
Source to target mapping 01Reconciliation & validation 02Defect tracking & resolution 03
02 / ENTERPRISE DATA2025 — PRESENT

Confidence in every record.

Data quality and migration testing across 10,000+ employee records at Stanford University.

Data validationPower BIOracle HCM
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My contribution

Define mapping logic and quality rules, reconcile PeopleSoft data with Oracle HCM outputs, investigate discrepancies, and document defects with HRIS and IT teams.

Stakeholder visibility

Built Power BI dashboards covering 1,000+ employee records to track data health, negative balances, cleansing progress and pay group trends.

This overview describes my work without displaying employee data or internal systems.

PERSONAL PROJECT / BUILDING IN PUBLIC
raw → refined.
raw_data.jobs↓staging models↓analytics marts
dbt + BigQuery / In progress
03 / ANALYTICS ENGINEERINGIN PROGRESS

Job data. A clearer picture.

Building a dbt and BigQuery project to transform raw job listings into documented, analytics ready models.

dbtBigQuerySQL
See the build plan +

Current foundation

Started with a raw_data dataset and jobs table in BigQuery, loading a sample jobs CSV and exploring the schema.

What comes next

Build staging models to standardize fields, add data quality tests and documentation, then develop analytics marts for job market exploration.

Models, results and a repository link will be added as the project develops. The diagram shows the intended workflow.

04 / NORTHWESTERN MUTUAL2022 — 2023

Shared metrics.
Sharper decisions.

Standardized tracking and reporting across 30+ Adobe Analytics report suites, with 15 dashboards for campaign performance, engagement and business KPIs.

Adobe AnalyticsData governanceKPI reporting
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Aligned event tracking, metric definitions and tagging rules. Analyzed 100,000+ digital events, helped stakeholders access insights 4× faster, and supported an 18% improvement in targeting precision.

15dashboards built

Turning recurring questions
into accessible answers.

05 / WHAT’S NEXT

The next chapter is loading.

A new project will live here. Details coming as the work takes shape.

PLANNED
A LITTLE ABOUT ME

Curious by nature.
Builder by practice.

I’m Pranav, a data engineer based in the Bay Area. I’ve built AI powered pipelines at QuickCruit, supported enterprise data quality at Stanford, and helped teams make sense of their analytics at Northwestern Mutual.

I like getting into the details: where the data came from, why a value looks wrong, and how to make the next run more reliable. Right now, I’m expanding my work in dbt, data modeling and cloud warehouses.

UC RIVERSIDE

B.S. Business Information Systems · 2024

MY TOOLKIT

Build & transform

Python / SQL / ETL / Vertex AI / Gemini

Store & structure

MongoDB / MySQL / PostgreSQL

Validate & communicate

Data quality / Power BI / Excel / Git

Currently exploring

dbt / BigQuery / Snowflake / Dagster

LET’S BUILD SOMETHING USEFUL

Your next data hire?
Let’s talk.↗

dadipranav@gmail.com ↗LinkedIn ↗Download resume ↓