Akshitha Bedre Shivakumar

Data Engineer & AI Enthusiast

I build data systems that get smarter over time. With 3+ years of experience crafting scalable ETL pipelines and integrating AI into cloud infrastructure, I transform complex data challenges into intelligent solutions.

Let's Connect View My Work
3+
Years Experience
65%
Migration Time Reduced
5TB+
Data Processed

Technical Expertise

Programming Languages

Python
SQL
Java
Scala

Big Data Technologies

Apache Spark
Apache Airflow
Apache Kafka
Hadoop

Cloud Platforms

AWS
Snowflake
GCP
Azure

Specializations

ETL/ELT Pipelines
Cloud Migration
MLOps
Infrastructure as Code

Professional Journey

AI Engineering Intern
DartIq.AI
February 2025 - May 2025
Contributing to Veemigrate development, reducing cloud migration planning time by 65% through AI-powered VMware-to-Cloud migration platform. Designing agentless migration pipelines and collaborating with LLM modeling teams to optimize cloud landing zones.
Data Engineer
Accenture
August 2022 - July 2023
Built and deployed enterprise-scale ETL/ELT workflows improving system performance by 30%. Automated data ingestion pipelines and monitoring scripts, reducing manual reporting by 80% and increasing analytics workload efficiency by 40%.
Junior Data Engineer
Accenture
January 2021 - July 2022
Built and managed batch and real-time data ingestion workflows using Python, SQL, and Apache Airflow. Maintained 99% uptime on production pipelines and developed cloud-native pipelines for seamless AWS transitions.

Featured Projects

🚌
Real-Time Transit Data Pipeline
Designed real-time data pipeline streaming live CTA bus data using Apache Kafka, Spark Structured Streaming, and Snowflake. Built interactive Streamlit dashboard with geospatial mapping and anomaly detection.
Apache Kafka Spark Streaming Snowflake Streamlit
🔍
Chicago Crime Data Analysis
Developed scalable ETL pipelines using Apache Spark and Hadoop to process 6+ million crime records. Applied Random Forest models for prediction and conducted geospatial analysis for public safety insights.
Apache Spark Hadoop Random Forest GeoPandas
🤖
End-to-End MLOps Pipeline
Engineered modular ML pipeline handling class imbalance and feature redundancy, increasing preprocessing efficiency by 45%. Applied SMOTE and PCA techniques, boosting model performance by 30%.
MLOps SMOTE PCA ONNX

Let's Connect

Ready to build something amazing together? Reach out and let's start the conversation.

✉️
Email Me
akshithabedre05@gmail.com
💼
LinkedIn
Let's connect professionally
💻
GitHub
Explore my code
📞
Call Me
+1 (872) 279-9971