Venkata Kanishka Vardhan Yedida
Hyderabad
Summary
Objective : Data Engineer with 2+ years of hands-on experience in building scalable data pipelines and processing large datasets using Python, PySpark, MySQL, AWS, and Big Data technologies. Eager to contribute to impactful projects while growing in Big Data systems and LLM-based applications. Looking to leverage my skills to drive data-driven decisions and continuous improvement.
Overview
2
2
years of professional experience
3
3
Certificates
Work History
Data Engineer
Virtual mark consultancy PVT LTD
01.2023 - Current
- Worked at AstraZeneca company as a contract employee.
- As a member of the Data Engineering team at AstraZeneca, I played a pivotal role in the AZ Brain project, managing and transforming data for enhanced operational insights.
- Leveraging Python and SQL within an AWS environment, I engineered robust data pipelines using Step Functions, ensuring seamless data flow from S3 to Elasticsearch.
- Implemented PySpark for ETL tasks and data transformations.
- Processed, manipulated, stored, and parsed data in 10+ data pipelines.
- I translate business needs into effective code solutions, bridging the gap between technical and business objectives. Engaging with sales representatives.
My responsibilities included :
- Creating and optimizing Step Functions for efficient data processing, focusing on prostate cancer and H1 data applications including LLM agent applications.
- Converting raw data into consumable formats and integrating it into Elasticsearch for API and UI consumption.
- Managing diverse datasets, including H1data and cancer data, while also handling universal raw NPI data for storage in PostgreSQL
- Additionally, I worked on a supporting internal app called ChatIQ, where I applied basic prompt engineering skills to create agents and summarization.
- Built a GenAI agent that generates SQL queries based on user prompts about drug sales and HCP influence, running them on pre-engineered, filtered datasets.
- The agent summarizes results and suggests follow-up questions for an interactive, context-aware user experience.
- Ensuring timely and consistent data availability for oncology and non-oncology apps across regions.
- Through my contributions to the AZ Brain project, I demonstrated my proficiency in data manipulation, pipeline development, LLM prompting and AWS services.
Education
B.Tech - Computer Science
Vishnu Institute of Technology
Bhimavaram, India06-2022
Diploma - Computer Science
Prasiddha College of Polytechnic
Amalapuram, India04-2019
10th class -
Vidyanidhi High School
Amalapuram, India03-2016
Certification
- AWS Certified Cloud Practitioner
- Python for Data Science – Coursera
- Snowflake Essentials Training
Timeline
Data Engineer
Virtual mark consultancy PVT LTD
01.2023 - Current
B.Tech - Computer Science
Vishnu Institute of Technology
Diploma - Computer Science
Prasiddha College of Polytechnic
10th class -
Vidyanidhi High School
Additional Information
- Attended an immersive NVIDIA AI workshop hosted by Astrazeneca company.
- Participated in poster presentation during college fest , Yuva sankalp 2019
Workshop
Attended an immersive NVIDIA AI workshop hosted by our company.
Skills
- Pyspark
- MySQL
- AWS (S3, EC2, Step Functions, EMR, RDS,Glue & Athena)
- LLM Prompting
- ETL development
- Data warehousing
- Python
- Elasticsearch
- Snowflake
- Java
social network
LinkedIn url: www.linkedin.com/in/yedida-venkata-kanishka-vardhan-9020a0179
Hobbies
- Photography
- Listening to music
- Sports
- Tech Enthusiasm
Development & Collaboration Tools
- GitHub – for code versioning and team collaboration
- Jira – for issue creation & tracking
- Confluence – for documentation
Soft skills
- Problem-solving and analytical thinking
- Clear communication
- Business-to-technical translation
- Quick learner and adaptable
- Team collaboration and coordination
Projects
Project: AZ Brain – Oncology & Non-Oncology Data Intelligence
Client: AstraZeneca
Role: Data Engineer
Tech Stack: AWS, PySpark, PostgreSQL, Elasticsearch, Python, SQL
Description : AZ Brain is a global business intelligence platform designed to support AstraZeneca's oncology and non-oncology initiatives. The system empowers regional stakeholders to track drug performance, doctor engagement, treatment statistics, and clinical metrics across cancer and H1 applications.
Built using scalable data engineering pipelines and robust ETL workflows, the platform integrates large datasets from multiple sources and delivers insights through APIs and UI dashboards. It combines data science, engineering, and cloud technologies to ensure accurate and actionable reporting for strategic decisions.
An internal LLM-powered tool, ChatIQ, was integrated to enhance app usability. Developing a GenAI agent that dynamically generates SQL queries on filtered datasets, summarizes drug and HCP insights, and suggests contextual follow-up questions, and improved navigation across all AZ Brain applications, ensuring a seamless stakeholder experience.
Project: Reservoir Water Level Forecasting using machine learning.
Description : Uneven rainfall and climate changes have adverse effects on reservoir water levels and have caused disasters in the past. Poor water management may lead to significant socio-economic losses. Forecasting the inflow and water level of the reservoir based on the past data(by considering various factors) helps us to prepare in advance to tackle any extreme conditions. This is an attempt to make use of time series analysis to predict water level at reservoir and hence provide better management.
Role : Worked as a team Member, Performed data preprocessing and gathered dataset.
Technology : Python, Streamlit.
Professional Summary
Exceptional Data Engineer with experience turning raw data from multiple sources into insights.
Skilled in delivering business insights and supporting LLM-based apps through clean, scalable data solutions.
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