Anup S.

Slow, unreliable, or expensive data pipelines cost you time and money — and most teams don't realize how much until reporting breaks or cloud bills spike. I help companies fix that by building fast, well-architected data platforms on Snowflake. I'm a Snowflake Data Engineer with 8+ years in cloud data engineering, including 4+ years hands-on building production data platforms on Snowflake. SnowPro Certified, with deep expertise in Python, dbt, Airflow, and AWS — I design ELT pipelines and analytics platforms that are reliable, cost-optimized, and built to scale. My work spans the full lifecycle: designing warehouses and pipelines from scratch, migrating legacy systems onto Snowflake, and optimizing performance and cost on platforms that were already live — on more than one project, that optimization work meaningfully cut query times and warehouse spend for teams stuck on inefficient setups. I build the transformation and orchestration layers (dbt, Airflow) that make data reliably usable, backed by data quality checks so issues get caught before they reach a dashboard. Core Expertise ✅ Snowflake Data Warehouse Design & Implementation ✅ Python-Based Data Engineering & Automation ✅ ELT/ETL Pipeline Development ✅ dbt Development & Analytics Engineering ✅ Snowflake Performance & Cost Optimization ✅ Data Modeling (Star Schema & Dimensional Modeling) ✅ Apache Airflow Workflow Orchestration ✅ AWS Data Engineering Solutions ✅ Data Migration & Modernization ✅ Data Quality, Validation & Monitoring Whether you're implementing Snowflake for the first time, migrating from a legacy platform, optimizing an existing data warehouse, or building modern ELT pipelines, I can help deliver a scalable data platform that supports both current needs and future growth.