Prayank Kumar

Data & Cloud Engineering | 2x Microsoft Certified | Azure | Fabric | Databricks | SQL | PySpark | ADF | Power BI | Github | Jenkins | Terraform | Bicep | National-Level Hackathon Winner

Data Engineer working across the Microsoft data ecosystem, with experience in Microsoft Fabric, Databricks, Synapse, Azure Data Factory, Snowflake, SQL, Python, and PySpark. I build scalable, governed data platforms that turn fragmented data into trusted, actionable insight. I’m also developing hands-on expertise in cloud engineering and infrastructure automation, using Azure, GitHub, Terraform, Bicep, and Infrastructure as Code to support cloud environments and streamline delivery. Core skills include MS SQL Server, MySQL, Azure SQL Database, Delta Lake, Pandas, NumPy, Scikit-learn, Matplotlib, and Power BI.

Work Experience

  • Cloud Engineer I

    • Insight Enterprises, Noida

    Oct 2026 - Present

  • Data Engineer Trainee

    • Insight Enterprises, Noida

    Apr 2026 - Sept 2026

    Completed my apprenticeship as a Data Engineer Trainee at Insight. This experience strengthened my foundations in SQL, PySpark, Microsoft Fabric, Databricks, and Azure while deepening my understanding of modern data ecosystems.

  • Data Engineer Intern

    • Vision Group, Noida

    June 2025 - Aug 2025

    Designed and maintained ETL pipelines using MS SQL and Azure Data Factory to automate data processing. Built Power BI dashboards by integrating multiple data sources and worked with clients to deliver data-driven insights.

  • Data Science Intern

    • CodSoft, Kolkata

    May 2025 - June 2025

    Built regression models for movie ratings and retail sales forecasting, and classification models for fraud detection. Utilised data preprocessing, feature engineering, and model evaluation techniques.

  • Marketing Data Analyst

    • FuzeMee, USA

    May 2023 - June 2023

    Collected and analysed user engagement data to access the performance of marketing campaign across digital platforms. Designed a data-driven marketing strategy using A/B testing and user feedback to improve app visibility & engagement.

Papers

Object Detection in Adverse Weather Conditions

This experiment uses the DAWN dataset, which contains images of road scenes captured under various adverse weather conditions such as fog, rain, snow and haze. As expected, these types of conditions were detrimental to edge detection and reduced the contrast of objects in the image making them difficult to detect.

Caption Generation using Machine Learning

This research paper aims at reviewing the area of machine learning based caption generation with reference to computer vision and natural language processing. It includes a comparison of the error rates of CNNs, RNNs, and Transformer models in the process of generating timely and descriptive captions of images.

Certifications

DP-700: Fabric Data Engineer Associate

Microsoft

SQL for Data Science

University of California, Davis

Python for Data Science

Indian Institute of Technology, Madras

Data Science Foundations

IBM

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