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Omkyao1998/README.md

Hi, I'm Omkar Gokhale

Data Engineer and BI Analyst with 3+ years across EdTech, hospitality, financial services and retail. I build data pipelines, turn messy data into dashboards that people actually use, and teach data engineering to 100+ students.

  • Now: Data Engineer & Subject-Matter Expert at Newton School of Technology
  • Before: BI/Data Analyst at Crowne Plaza Dublin Airport and Atos Syntel
  • Education: MSc Data Analytics, Dublin City University
  • Certified: Microsoft Power BI Data Analyst (PL-300) · AgilePM Practitioner
  • Learning: Databricks, Snowflake, dbt and cloud data platforms

What I work with

Area Tools
Data engineering Python, SQL, PySpark, ETL/ELT, SSIS, data warehousing
Analytics & BI Power BI (DAX, Power Query, data modelling), Tableau, Excel
Databases & cloud PostgreSQL, SQL Server, MongoDB, Hive, Azure, Git
Machine learning scikit-learn, clustering, classification, forecasting

Featured projects

Project What it does Stack
Retail & Warehouse Sales ETL End-to-end pipeline that cleans sales data and produces 16 report tables: trends, top suppliers, MoM growth, channel comparison PySpark
Football Player Similarity Finds players with similar profiles for scouting, explained with SHAP Python, Keras, SHAP
Product Category Classification Predicts product category from listing text on 245K Etsy products (89% validation accuracy) Python, NLP, scikit-learn
Airbnb Superhost Prediction Cleans 256K listings from 31 US cities and models Superhost status Python, scikit-learn
Spotify Genre Analytics Collects 50K tracks via the Spotify API and maps how genres differ in sound Python, Spotify API, PCA

Impact at work

  • Built PySpark pipelines processing 1M+ records, cutting reporting turnaround by 10%
  • Used customer and supply-chain analytics across three hotels to help drive a 15% revenue increase
  • Centralised 5M+ records from several source systems into one data warehouse

Contact

LinkedIn · omkarg100998@gmail.com · Pune, India (open to relocation)

Pinned Loading

  1. E-Commerce-PySpark E-Commerce-PySpark Public

    A PySpark-based ETL and analytics pipeline for retail and warehouse sales data. It handles ingestion, cleaning, transformation, advanced aggregations, window-function analysis, and exports results …

    Python

  2. AirBnb_Data_Analysis AirBnb_Data_Analysis Public

    Superhost prediction on 256K Airbnb listings from 31 US cities: data cleaning, Lasso imputation and 5 classifiers

    Jupyter Notebook

  3. Football_Player_Similarity_Analysis Football_Player_Similarity_Analysis Public

    This project applies Cosine Similarity and a Neural Network Autoencoder to evaluate football player similarity based on position-specific features. Using SHAP (SHapley Additive exPlanations), the s…

    Jupyter Notebook

  4. Product_Category_Classification Product_Category_Classification Public

    Predict Etsy product category and colour from listing text (245K products, NLP + scikit-learn)

    Jupyter Notebook

  5. Spotify_Genre_Analytics Spotify_Genre_Analytics Public

    Collect 50K Spotify tracks across 150+ genres via the Spotify API and explore audio features with PCA

    Jupyter Notebook