Candidate CTOMT12048
none
Not specified
20-03-2026 7:30 AM
English, Full-time
yes
per direct
N/A
KATTAMURI PADMAVATHI
Visa Status: HSM Dependant, valid until 20.04.2028
Phone: +31 622121023
Address: South Holland, Netherlands
Email: padmavathi.kattamuri2001@gmail.com
LinkedIn: www.linkedin.com/in/padmavathikattamuri
Junior Data Engineer | GCP, Python, SQL, AI & Machine Learning
Junior Data Engineer with 1.8 years of professional experience and academic background in Computer Science, supplemented by hands-on expertise in Google Cloud Platform (GCP), Python, SQL, and BigQuery. Demonstrates proficiency in developing data-driven solutions and implementing Gen AI models for advanced analytics.
Certified in Python, HTML, and Salesforce, with an aptitude for learning new technologies and adapting quickly. Actively seeking opportunities in the Netherlands market and continuously improving language proficiency in Dutch (A2 level) for better integration into local culture.
KEY HIGHLIGHTS
• Technical Proficiency: Expertise in Google Cloud Platform (GCP), BigQuery, Python, SQL, and Data Analytics.
• Industry Experience: Hands-on experience in AI-powered object detection and machine learning model implementation.
• AI & Machine Learning: Developed AI models for object detection and package type identification in real-world applications.
• International Exposure: Prior experience working in the EU region, contributing to projects related to AI and data analytics.
• Communication Skills: Effective communicator with a team-oriented mindset and a commitment to problem-solving and collaboration.
PROFESSIONAL EXPERIENCE
Accenture – Data Engineer
Feb 2024 – Oct 2025 | Chennai, India
• Worked on AI-driven parcel analytics solutions for a UK-based logistics client using Google Cloud Platform.
• Developed a GenAI-based Proof of Concept for double item detection using Gemini multimodal models on Vertex AI, applying prompt engineering techniques.
• Designed structured system prompts and reasoning instructions to ensure accurate parcel identification from grayscale parcel images.
• Built a Python-based pipeline to process parcel images from Google Cloud Storage and perform automated inference using Vertex AI.
• Implemented an image analysis solution for package type identification, classifying parcel types such as polybag, GP packaging, and carton boxes.
• Developed data pipelines and analytical workflows using BigQuery, working with logistics datasets to generate insights for operational planning.
• Performed data analysis and forecasting using BigQuery to explore historical parcel datasets, supporting logistics decision-making.
Achievements:
• Gained hands-on experience with GCP services, including BigQuery, Vertex AI, and Cloud Storage.
• Successfully delivered a PoC for double item detection and package type identification, which was approved for further development toward production.
• Improved understanding of GenAI prompt engineering techniques for image-based parcel classification tasks.
• Developed analytical insights from logistics data to support parcel demand forecasting and operational planning.
KEY SKILLS
• Programming Languages: Python, C, C++
• Cloud Platforms: Google Cloud Platform (GCP), AWS Cloud
• Databases & Data Engineering: MySQL, BigQuery, SQL
• AI & Machine Learning: Vertex AI, Gen AI Models, Gemini Model
• Data Analysis & Visualisation: Pandas, Numpy, Matplotlib
• Tools & Frameworks: Jupyter, PyCharm
• Prompt Engineering: Generative AI, Gemini Models
PROJECTS
Double Item Detection using Gemini (GenAI)
Scope: Developed a GenAI-based solution to detect whether parcel images contain single or multiple parcels using Google Vertex AI Gemini models.
Contribution:
o Implemented few-shot prompting (10-shot) with Gemini multimodal models to classify parcel images as Single or Double.
o Designed structured prompts to guide the model in identifying parcel boundaries and separation.
o Built a Python-based inference pipeline to process parcel images from Google Cloud Storage (GCS).
o Integrated Vertex AI Gemini (gemini-2.0-flash) for image analysis and generating structured responses.
o Conducted experiments and prompt refinements to improve classification accuracy.
Result:
o Successfully validated the Proof of Concept (PoC), which was approved for further implementation toward production.
Package Type Identification
Scope: Developed an image-based solution to identify parcel packaging types such as polybag, GP packaging, and carton boxes.
Contribution:
o Conducted multiple experiments using computer vision approaches, including YOLO, during early development.
o Applied image preprocessing techniques to improve parcel image quality and model detection performance.
o Evaluated different approaches for parcel classification, supporting automated sorting.
o Collaborated with the data science team to test models on real logistics datasets.
Result:
o Successfully validated the Proof of Concept (PoC), which was approved for further implementation toward production.
CERTIFICATIONS
• Cisco – Programming Essentials in Python
• IIT Bombay – HTML
• Salesforce Developer Virtual Internship
• Coursera University of Michigan – Python Programming
• Coursera Google Cloud – Digital Transformation
• AWS Academy – ML and Cloud Foundations
• Smart Internz – Salesforce Developer Virtual Internship
• COGEDS Orai – AI-Powered Communication Coach (Grade A)
EDUCATION
• Bachelor of Technology in Computer Science and Engineering
Lendi Institute of Engineering and Technology | 2023
STRENGTHS
• Strong problem-solving and analytical abilities.
• Eagerness to learn and adapt to new technologies.
• Excellent communication and collaboration skills in diverse team settings.
• Self-motivated with a positive attitude toward overcoming challenges.
LANGUAGES
• English, Telugu and Dutch (A2 Level)