Hitesh Taneja

AKA. Happy :)

Hi, I’m Hitesh. I am a Data Engineer with professional experience at Accenture and as a Freelance Data Consultant. I specialize in moving massive datasets, optimizing SQL for performance, and building the backend infrastructure that powers modern applications. While I have a strong academic background in AI/ML, my career focus is on the engineering backbone—pipelines, APIs, and production-grade code—that makes data useful.

Originally from India, I’ve always been passionate about using technology to create useful, impactful solutions for the internet. Whether it’s data analysis, web development, or software engineering, I love turning raw data into insights that can change the world.

When I’m not immersed in research or coding, you can find me sharing my experiences and learnings on Medium, beatboxing, or exploring the outdoors through traveling and hiking. I also enjoy spending quality time with family and friends, listening to music, and diving into self-help books.

Welcome to my digital space-a place where data meets creativity, and every project is a step toward making a positive impact.

• LinkedIn @hiteshtanejaa (opens in a new tab)
• Twitter @hiteshtanejaa (opens in a new tab)
• GitHub @hiteshtanejaa (opens in a new tab)
• Scaler @Hitesh Taneja (opens in a new tab)
• Email hiteshtanejaa@gmail.com

Work

So if are till here I think you are interested to know what I WORK on:

What I've been working on

I am diving into the intricacies of unsupervised learning by focusing on cluster interpretation via dimensionality reduction. The project explores the challenge of making sense of high-dimensional data by projecting it into a lower-dimensional space without losing the core characteristics that define distinct clusters. I am developing novel methodologies that not only preserve the structure of the data but also provide intuitive visual representations for interpretation. By leveraging advanced techniques such as t-SNE and UMAP alongside traditional approaches like PCA, I aim to uncover hidden patterns that conventional clustering methods might miss.

This work is especially crucial in applications where understanding the underlying data distribution can lead to better decision-making, such as in customer segmentation, anomaly detection, and bioinformatics. The research involves rigorous experiments on diverse datasets, rigorous evaluation metrics, and iterative refinement to ensure that the reduced dimensions accurately reflect the intrinsic relationships within the data.

Ultimately, this project seeks to bridge the gap between complex data analytics and human interpretability, enabling data scientists and stakeholders to derive actionable insights with greater clarity. It’s an exciting journey of blending theory with practical solutions that demonstrate the power of artificial intelligence in transforming raw data into meaningful, visual narratives.

Accenture

Title: Data Engineer (Client: NatWest Group) In 2022, I joined Accenture as a Data Analyst, and then progressed to become an Data Engineer Engineer, where I had the opportunity to collaborate on a critical project for an Irish financial institution. Our mission revolved around supporting the bank’s strategic closure of 63 branches — a massive initiative that required intelligent automation, secure data handling, and smart analytics.

Core Engineering:

• Data Pipeline Automation: Developed and maintained critical ETL workflows using PySpark and SQL, automating manual reporting tasks and scheduling jobs via Autosys.

• Backend Development: Built high-performance backend services using FastAPI to support internal knowledge systems, reducing data retrieval latency for business users.

• System Reliability: Took ownership of job failure resolution and package deployment (SSIS), ensuring high availability for banking data services.

• Infrastructure: Implemented CI/CD pipelines and Git workflows to streamline code deployment across dev and production environments.

Innovation & AI Integration:

• Bridged the gap between data engineering and data science by architecting the retrieval infrastructure for a RAG-based internal tool, utilizing Vector Databases to serve unstructured data to LLMs.

Before Accenture, I worked as a Freelance Data Consultant.

• Query Optimization: Re-engineered complex SQL queries (Window Functions, Joins) to process smart meter data, improving report generation speed by 40%.

• Data Quality: Built automated data validation scripts that reduced downstream errors by 25%, ensuring accuracy for the Meter Data Management System (MDMS).

• Visualization: Designed interactive Tableau dashboards to track device reliability and consumption trends for executive decision-making.

Prior, I was working as a Tutor at StudyPool and also as Freelance Web Developer. I worked with 3 small business to help them bring their business online.

if you ever liked working with me or my work or just me being me

you can consider buying me a coffee

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