Rohit B.

Data Engineer | ETL Pipelines, Data Warehousing, BI Dashboards

⚡ Data pipelines breaking, slow, or too expensive? That’s exactly what I fix. I help companies turn messy, unreliable data systems into scalable, high-performance pipelines — so teams can actually trust their data and move faster. Over the past few years, I’ve built and optimized data platforms handling 50GB/day streams to 500GB+ processing workloads, across ecommerce, fintech, real estate, and SaaS. 🔑 What I Deliver (Real Outcomes, Not Just Tools) 🔹 Robust ETL/ELT Pipelines: Built on AWS Glue, Azure Data Factory, Databricks, Airflow → Designed for zero-failure execution & recovery-safe architecture 🔹 Cloud Data Warehousing: Redshift, Snowflake, BigQuery, Azure Synapse → Structured for fast queries, low cost, and scalable analytics 🔹 Real-Time & Batch Processing: PySpark, Kafka, Delta Lake → Handling millions of records daily with optimized latency 🔹 AI-Ready Data Foundations: → Clean, structured pipelines ready for ML models, LLMs, and BI tools. 🔹 Performance Optimization: → Reduced processing time by 50% on production workloads → Optimized queries & pipelines saving compute cost + runtime 🔹 Business Intelligence Layer: Power BI, Looker Studio → Dashboards that leadership teams actually use for decisions. 📦 Proven at Scale:- 🏪 Ecommerce Data Platform (1M+ stores | 500K customers): Built end-to-end ETL pipelines using AWS Glue Implemented incremental (delta) processing across multiple data sources Designed Redshift warehouse for high-volume analytics Delivered Power BI dashboards for business insights ✅ Enabled AI-driven personalization for 100K+ active users ✅ Reduced manual data dependency across teams 💳 FinTech / Freight Billing AI Platform: Designed data infrastructure for AP/AR automation Integrated ERP + TMS systems via APIs Built real-time dashboards + audit tracking ✅ Improved financial visibility & reconciliation accuracy ✅ Enabled automated decision-making for cash flow optimization 🏠 Real Estate Data Intelligence Platform: Built pipelines ingesting: Zillow Realtor HUD Census Crime datasets Centralized into PostgreSQL + Azure Data Warehouse ✅ Computed ROI, NOI, Cap Rate, Cash Flow at scale ✅ Enabled investment decision analytics 📊 Retail Location Intelligence (Databricks / Snowflake): Processed ~500GB mobile location data Built anomaly detection using moving averages ✅ Automated detection of: data drops duplicates false entries 🔧 Logistics Optimization (Azure): Replaced upsert with SQL MERGE ✅ Reduced processing time by 50% ✅ Achieved zero data loss in production pipelines 📡 Wellness Data Platform: Consolidated fragmented APIs into unified pipelines ✅ Fixed data failures on 250MB+ tables (~1GB compute load) ✅ Improved data consistency and pipeline reliability