Hey, I’m Prayag Padwal, a data engineer who’s all about turning raw data into something that actually matters—fast and at scale. For the last 5+ years, I’ve been knee-deep in data platforms, working with Fortune-500 utilities, public universities, and startups that move quick. My thing? Building systems that don’t just crunch numbers but deliver insights that hit the bottom line—like catching a $2 million revenue leak before it became a problem or slashing pipeline runtimes by up to 89%. At PG&E, I rebuilt their Redshift warehouse, taking nightly refreshes from a painful 90 minutes to under 15. At Cal State Long Beach, I crafted PySpark pipelines to wrangle 500k+ student records, spotting patterns that improved retention forecasts. I’ve worked across 2 continents, speeding up ETL processes, moving clunky Oracle setups to clean star and snowflake schemas, and building dashboards that give decision-makers what they need, when they need it. Here’s what I bring to the table: Cloud & Storage: AWS (Redshift, S3, Glue, Lambda), Snowflake, Databricks Workflows & Automation: Apache Airflow, dbt, Docker, GitLab CI Big Data & Pipelines: PySpark, Python (cx_Oracle, pyodbc), SQL (Oracle, Postgres, MS SQL) BI & Visualization: Tableau, QuickSight, Power BI; I’m handy with DAX and custom analytics apps How I Work: I’m all about clean data models (star/snowflake), performance tuning, and automated testing to keep things tight. Outside the tech, I’m a 2x Datathon champ, hold AWS and Tableau certs, and co-founded a nonprofit to give back. I also write on Medium, where 100k+ folks read my stuff every month, and I mentor aspiring data engineers to help them find their footing. Let’s build something that doesn’t just process data but makes an impact.