Abhishek Anand

Data Engineering | Distributed Systems | Building with AI

Mechanical Engineering graduate who transitioned into software engineering. Passionate about coding, learning new technologies, solving challenging problems, and building robust solutions.

Latest Blog Post

There are no Purely Interpreted Languages Anymore

May 9, 2026

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Experience

Software Engineer | Data Engineer

April 2024 - Present

Apple (Contractor)

• Worked on the Apple Maps Product
• Technologies used: Spark, Scala, Snowflake, S3
• Wrote complex and optimized Spark tasks for data processing
• Orchestration Client and Spark Tasks for long running jobs
• Analysing and Debugging Maps geometric data
• Ran jobs on EMR and EKS clusters
• Ran SQL queries on Snowflake

Software Engineer

June 2021 - April 2024

HCL Technologies Limited (HCL)

• Spearheaded Angular-Java Full Stack development, contributing to UI and API development, unit testing, debugging, and code refactoring.
• Demonstrated coding skills by writing and debugging over 30,000 lines of code.
• Took ownership of the crucial Run profile module, enhancing diagnosis and research efficiency.
• Implemented the software update functionality for the desktop version of the software.
• Innovated a utility software for generating update patches, automating processes, and minimizing error susceptibility.
• Successfully implemented Data purge functionality in a microservices based application, optimizing data management.
• Achieved 90% test coverage by creating and executing 500+ test cases, significantly reducing defects.

Projects

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Roche LightCycler Project

Worked on LightCycler Software at HCL Technologies - a desktop application using Electron with Java and Angular for medical device data processing.

Java Angular Electron Spring Boot Docker Finite State Machine Rabbit MQ Plotly

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Word Sudoku

An Angular-based word game with Dictionary API integration and a scoring system based on completion time. Deployed on Netlify.

Angular TypeScript HTML CSS Dictionary API

GitHub View details

Rain/no-rain classification from combined Radar - Radiometer data using Machine Learning

Machine learning project using Neural Nets and Random Forest to classify rain/no-rain signals. Improved F1 score from 0.59 to 0.65 baseline.

Python Machine Learning Neural Nets Random Forest scikit-learn

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Skills

Git Java Spring Boot Docker Kubernetes SQL Python Scala React Tailwind CSS Angular Data Engineering

Education

IIT Bhubaneswar

Dual Degree (BTech + MTech) in Mechanical Engineering

Jun 2016 – May 2021 CGPA: 8.2

MCM Scholarship (Merit-based academic scholarship)