Mayank Joshi

About Mayank Joshi

My journey into data didn’t begin with algorithms or dashboards—it began with curiosity…

Experience

1. Data Engineer

   McKesson

   Nov 2024 — Present

   Engineered scalable real-time and batch data pipelines by leveraging Apache Spark, Kafka, and Airflow, enabling seamless integration of transactional, logistics, and IoT data streams to support analytics and machine learning use cases.• Developed a centralized Feature Store using Feast and Databricks, ensuring consistent, reusable, and version-controlled features across machine learning training and inference, which reduced redundant feature engineering efforts by 30%.• Optimized enterprise data storage by implementing a Delta Lake architecture on AWS S3, improving query performance by 40% and cutting storage costs through efficient use of Parquet-based compression and partitioning.• Implemented a robust data quality framework with Great Expectations and Amazon CloudWatch, establishing automated anomaly detection and schema validation that improved upstream data reliability by 25%.• Orchestrated complex workflows with Apache Airflow, incorporating task retries, lineage tracking, and dependency management, which reduced pipeline downtime and manual interventions by 20%.• Collaborated with data science and business teams to deliver ML-ready datasets and real-time features, accelerating demand forecasting and inventory optimization projects and directly contributing to improved supply chain efficiency.

Education

• Rajiv Gandhi Prodyogiki Vishwavidyalaya

  Bechalor in Engineer in electronics and communication

• Pace University

  Master of Science - MS

  2023 — 2025