Data Engineer | MS Data Science @ GWU (GPA 3.9) | Washington, DC

I design and build robust data pipelines and warehousing solutions that transform raw data into actionable insights. With 2+ years of hands-on experience in ETL, data modeling, and real-time processing, I've optimized workflows to reduce latency by 30% and ensured data accuracy across enterprise systems.

I'm a data engineer passionate about building efficient, scalable data infrastructure. Starting my career at Tata Consultancy Services (TCS), I developed expertise in SQL, ETL pipeline design, and data warehousing using Star Schema. Now, I'm leveraging Python, PySpark, and advanced analytics to solve complex data challenges at scale.

Data Engineering: ETL Pipeline Design · Data Warehousing (Star Schema) · Data Modeling · Real-time & Batch Processing · Automated Data Validation
Languages & Databases: SQL (Advanced) · Python (Pandas, PySpark, OpenCV) · Java · SQL Server · MongoDB
Tools & Platforms: Informatica Cloud · Git · Linux · Docker · Jira · Power BI
Certifications & Awards: Star of The Month (TCS) · OSPO Award (Real-Time Danger Detection System)

OSPO Award Winner

• Engineered a real-time computer vision pipeline using Python, OpenCV, and YOLOv3 to detect hazardous conditions
• Built automated notification system with instant alerts and visual evidence
• Recognition: OSPO Award and cash prize for technical innovation in public safety

• Designed a Star Schema data warehouse with optimized ETL procedures
• Created query-ready datasets for business intelligence and analytics
• Optimized data access and retrieval workflows for efficient query performance

• Analyzed 12+ million records using PySpark and Parquet to identify high-density traffic zones
• Implemented complex spatial transformation logic within ETL workflows
• Demonstrated capability with large-scale data processing and feature engineering

GWU Data Science Capstone · Aug 2025 – Present

• Designed a Reinforcement Learning (RL) pipeline to perform pseudo-labeling, improving downstream model accuracy compared to standard self-training baselines
• Automated the generation of high-confidence labels for unlabeled data, reducing reliance on manual annotation
• Benchmarked RL against non-RL approaches to quantify trade-offs in accuracy and efficiency, delivering a reproducible workflow

GWU, Washington, DC · Jan 2025 – May 2025

• Applied machine learning and transformer-based NLP models to classify math problems into eight categories
• Developed data preprocessing and evaluation pipelines for model comparison and reproducibility
• Documented methodologies and findings for academic dissemination

GWU

• Built Python-based thermal models to analyze sensible–latent heat storage systems and assess discharge efficiency
• Applied machine learning optimization to predict system performance under varying conditions
• Achievement: Paper accepted for poster presentation at the 7th Battery and Energy Storage Conference, 2025

GenAI / LLMs

• Developed end-to-end Generative AI pipeline using OpenAI models and LangChain to automatically generate transcripts, summaries, and viral clips from long-form video content
• Optimized system prompts to improve summarization accuracy and context retention by 20%

• Fabrication and Study of PCM-based Waste Heat Recovery System – POCER 2019, Nottingham University
• Thermal Energy Storage System Performance Using PCM-Variable Heat – POCER 2019, Nottingham University
• Paper accepted for poster presentation at the 7th Battery and Energy Storage Conference, 2025

• 🏆 OSPO Award – Real-Time Danger Detection System with cash prize
• ⭐ Star of The Month – Tata Consultancy Services (TCS)
• 🎓 Global Leaders Award – George Washington University (Scholarship)

Master of Science, Data Science
George Washington University, Washington, DC · December 2025
GPA: 3.9 | Honors: Global Leaders Award (Scholarship)

Operations Lead | Google Developer Groups
August 2024 – Present

• Directed the "Build with AI" conference with C-suite executives (CEOs/CTOs)
• Moderated executive panel on emerging tech trends and enterprise scalability
• Collaborated with university departments on ethical, inclusive technology learning

Volunteer | IEEE Student Chapter
January 2018 – May 2020 · JNTU, India

• Coordinated technical workshops and hackathons for 200+ participants
• Managed stakeholder communication and event scheduling

📧 Email: [email protected]
📱 Phone: 571-274-9816
💼 LinkedIn: https://www.linkedin.com/in/deepikardy7129
📍 Location: Washington, DC