Hrushikesh Joshi

About Hrushikesh Joshi

Driven by a passion for building scalable and efficient data and software systems, I specialize in designing and deploying robust, cloud-native architectures. With hands-on expertise in Python, AWS, and Apache Airflow, I thrive on solving complex challenges in data engineering, software development, and system optimization.In my current role as a Data Engineer at Community Dreams Foundation, I’ve architected ETL pipelines with Airflow to process structured and unstructured data, developed Kafka streaming workflows to handle millions of events per hour, and implemented efficient PostgreSQL solutions for sub-second query responses. My focus on scalable design and cost-efficient storage using S3 lifecycle policies and Parquet compression showcases my ability to blend technical proficiency with business impact.Previously, as a Software Developer at Datamann India LLP, I automated data pipelines, developed REST APIs, and engineered IoT solutions to enable real-time monitoring and seamless ERP integrations. I also excelled in containerized deployments using Docker and implemented Git branching strategies to streamline collaborative development.Through my personal projects, I’ve explored renewable energy optimization, predictive analytics, and energy economics, applying advanced statistics, machine learning, and real-time data integrations.I’m always excited to collaborate, innovate, and create impactful solutions. Let’s connect!

Experience

1. Data Engineer

   Community Dreams Foundation

   Aug 2024 — Present

   Designed normalized, cloud-native schemas for multi-terabyte OLTP systems, ensuring compatibility across environments.Built ETL pipelines in Apache Airflow to ingest/transform structured and unstructured data into a centralized data storage.Created Kafka streaming pipelines using schema registry/protobuf, ingesting millions of events/hour for real-time workflows.Optimized PostgreSQL with materialized views, partitioning, and indexing for sub-second query responses in key use cases.Engineered scalable validation systems with Great Expectations for schema checks, deduplication, and anomaly detection.Reduced storage costs with AWS S3 lifecycle policies, Parquet compression, and partitioning, improving storage efficiency.

Education

• Pace University - Seidenberg School of Computer Science and Information Systems

  Master's degree, Computer Science

• Savitribai Phule Pune University

  Bachelor of Engineering - BE, Information Technology