What I do
Design ETL pipelines, automate workflows, profile datasets, and build ML-powered tools that improve speed, quality, and decision-making.
Open to Data, AI, and Engineering opportunities
Building data products that scale.
I’m Atharva Upadhyay, an AI & Data Science student and Data Engineer Intern focused on ETL systems, analytics automation, and machine learning projects that turn raw data into useful decisions.
About
I work across data engineering, applied analytics, and machine learning with a strong interest in practical, production-ready systems.
What I work with
Python, SQL, PostgreSQL, Django, FastAPI, Airflow, Azure, AWS, Docker, Pandas, NumPy, and modern data tooling.
What matters to me
Clarity, scalability, measurable impact, and building systems that are as useful to people as they are technically sound.
Experience
Roles spanning data engineering, analytics, automation, and predictive modeling.
Data Engineer Intern • Nimbus Property Systems Ltd
- Designed and deployed ETL pipelines in Python, Scrapy, and PostgreSQL processing 2M+ records per day.
- Automated data profiling to detect anomalies, improving data quality by 35%.
- Integrated Azure Blob Storage and Azure SQL for distributed, cloud-native ingestion.
- Contributed in Agile sprints to improve collaboration and delivery velocity.
Selenium Django Developer • Medius AI
- Automated 90% of legal filings using Python, Django, and REST APIs.
- Built real-time data workflows processing 500+ filings per week.
- Developed scalable systems with 99.5% uptime for reliable delivery.
Data Analyst Intern • Careeriva
- Conducted data mining and cleansing from 50+ sources using Scrapy and Selenium.
- Engineered structured datasets in JSON, CSV, and SQL formats for advanced analytics.
- Reduced manual analysis time by 40% through workflow automation.
Research Analyst • Essmart
- Developed predictive models that improved product targeting accuracy by 15%.
- Analyzed 100K+ records to support business strategy with statistical insights.
- Worked across product and analytics teams using Python and NumPy.
Projects
A few projects that reflect my interest in NLP, recommendation systems, and applied machine learning.
NLP • Classification
News Summarization & Sentiment Analysis Tool
Built an NLP workflow using DistilBERT for sentiment prediction with 90% accuracy, while automating preprocessing, feature extraction, and inference.
Recommendation • Personalization
HarmonSync – Music Recommendation System
Designed a recommendation pipeline using feature engineering and similarity-based ranking, with a feedback loop to refine results iteratively.
ML • Fintech
Mutual Fund Recommendation System
Built an ML-based recommendation system aligned to user risk profiles, improving match rate by 25% through data-driven clustering and ranking logic.
Skills
Tools and technologies I use across engineering, analysis, and ML workflows.
Programming & Frameworks
Data & Cloud
Data Science
Working Style
Education
Devi Ahilya Vishwavidyalaya, Indore
M.Tech Dual Degree in Artificial Intelligence and Data Science
Certifications & Awards
- Google Analytics (Advanced)
- Google Cloud Foundations — Data, ML, AI
- Skill India Hackathon — Winner
- NCSC — Winner
- NCC A Certificate Holder