Prabhas Gupta

Frontend • Intern • Hyderabad, India • UTC+05:30 • Work permits: India, United States • Available now
Data Scientist
Active 5 days ago
+1 (470) 6096941
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Overview
Timeline
Roles

Overview

An early-career developer at the intern level with no human-authored frontend or application code available for detailed analysis. The only public hint of domain interest is a project description mentioning TensorFlow object detection, but that is not backed by human-authored source files. There is no evidence of frontend architecture, state management, testing, or performance work in the provided human-authored content.

Timeline

University of Illinois at Springfield
Master's Degree • Computer Science
2022–2023 Springfield, Illinois
Big Data & Hadoop Developer • Middle
i3 Infotech • Full-Time
Hyderabad In office
Developed distributed Spark processing applications in Scala and Python to ingest, clean, and process large datasets into HDFS. Implemented real-time ingestion with Apache Kafka and Spark Streaming, and used HBase for storing formatted packet data. Wrote HiveQL for optimized joins and built dimensional models for claims analytics. Designed batch workflows with Oozie, Sqoop, and Flume and managed Hadoop coordination via Apache ZooKeeper, while maintaining code quality using Git/GitHub.
Spark
Scala
Python
Apache Kafka
HBase
Hadoop
ZooKeeper
Git
pySpark
Financial Data Analyst / Gentax Developer • Middle
Illinois Department of Revenue • Full-Time
Springfield In office
Integrated financial and risk data from ERP systems, payment gateways, and external APIs into Azure-based data platforms. Developed SQL queries, stored procedures, and PySpark transformations for near real-time transaction processing and implemented SCD Type 1 and Type 2 for audit compliance. Designed incremental CDC pipelines with Azure Data Factory and secured secrets using Azure Key Vault. Monitored pipelines with Azure monitoring tools, ensured reliable storage with Delta Lake in Azure Databricks, and automated ADF notebook releases via Azure DevOps CI/CD.
Azure
SQL
pySpark
Spark
Delta Lake
Databricks
Azure DevOps
CI/CD
Data Engineer • Middle
Central Hudson • Full-Time
Poughkeepsie In office
Translated product requirements into automated cloud ETL pipelines by orchestrating multi-step workflows with Apache Airflow and Databricks Pipelines integrated with AWS Step Functions. Ingested data from relational and NoSQL sources into AWS S3 using PySpark over JDBC, and developed PySpark-based predictive models for risk modeling. Built streaming event ingestion with Apache Kafka and Spark Streaming, and implemented ELK dashboards with Elasticsearch, Logstash, and Kibana to monitor job execution. Automated deployments with Jenkins and Git and delivered analytics visibility via Looker dashboards on GCP BigQuery.
Airflow
Databricks
AWS
pySpark
Apache Kafka
Spark
ElasticSearch
Logstash
Kibana
Jenkins
Git
CI/CD
Google BigQuery
GCP
Python
Data Engineer • Middle
Abercrombie and Fitch • Full-Time
In office
Built and maintained scalable production ETL pipelines using Apache Airflow and Databricks Workflows for scheduled processing. Contributed to cloud architecture decisions, data quality initiatives, and observability tooling to keep pipelines maintainable. Developed ingestion pipelines from external APIs into cloud lakehouses and created ML-related pipelines in Databricks for claims risk scoring. Implemented Medallion Architecture with CDC processing, and set up CI/CD automation using Azure DevOps and Git.
Airflow
Databricks
Azure DevOps
Git
CI/CD
Intern Frontend Developer Confidence: Low Generalist
An early-career developer at the intern level with no human-authored frontend or application code available for detailed analysis. The only public hint of domain interest is a project description mentioning TensorFlow object detection, but that is not backed by human-authored source files. There is no evidence of frontend architecture, state management, testing, or performance work in the provided human-authored content.
UI Component Architecture
How interface parts are built
Not evidenced in public code
Responsive & Cross-browser
Works on all screens and browsers
Not evidenced in public code
Performance Optimization
Speed of the interface
Not evidenced in public code
Accessibility & Semantics
Usable for everyone
Not evidenced in public code
State Management & Data Flow
Managing data in the app
Not evidenced in public code
UX & Visual Polish
Look and feel quality
Not evidenced in public code
Recommendations
  • Work on small, well-scoped tasks such as dataset preprocessing scripts, reproducible Jupyter notebooks, or single-feature implementations under senior mentorship.
  • Contribute human-authored, focused frontend artifacts - for example a small React/Vue UI demonstrating data visualization and documented async state handling - so engineering judgment can be evaluated.
  • Add tests (unit and integration), clear commit messages, and small PRs that show ownership; include README sections mapping code files to features.
  • If interested in ML, publish a minimal end-to-end example that includes the model code, training script, and an inference demo with clear attribution of original files.
Repositories
The developer's experience in this domain has been verified based on AI analysis of the following repositories:
Machine-Learning-models