Harsh G.
Associate Engineer @ Shell | Microsoft certified Data Analyst and Data Engineer | Databricks certified Associate Data Engineer
- Role
- Associate Engineer at Shell
- Location
- New Delhi, DL, IN
- LinkedIn followers
- 500 followers
About Harsh G.
I am a Software and Data Engineer with hands-on experience in Python, SQL, Databricks…
Experience
Associate Engineer
Aug 2023 — Present · Bengaluru, IN
As an Associate Engineer at Shell, I contributed to the Shell Energy eMobility Project, where I developed 2 key data pipelines. I created 6+ Python notebooks covering multiple ETL stages and managed ingestion and transformation for 15+ tables using Databricks and AWS S3. I also migrated 10 critical reporting views from Google BigQuery to Databricks, ensuring seamless data integration and consistency. Additionally, I resolved 25+ bugs, implemented review feedback, and optimized pipeline performance and maintainability.In the Shell Mobility Project, I played a core role in enhancing two major Power BI dashboards. For the Capex Master Dashboard, I restructured it using DALPS templates, added 4 new pages, modified 2 existing ones, and created 16+ bookmarks with 6+ dynamic formatting rules. I worked closely with stakeholders to align visualizations with business needs. On the Non-EV Lease Management Dashboard, I focused on front-end improvements, optimized DAX queries, remodeled data models with 20+ relationships, and fixed 30+ complex DAX issues—greatly improving performance and usability.Under Shell Products & Chemicals (PnC) project, I managed ADF pipelines for yearly and ad hoc refreshes, handled Delta tables in Databricks, and ran scripts to calculate Product Carbon Footprints (PCF) across Shell chemical plants. I integrated new plant processes into the PCF model and developed a new calculation script for refinery products, creating the final SQL table structures and delivering a Power BI dashboard for refinery PCF insights. In Chemicals Data Platform (CDP) project, I handled ad hoc ingestion requests using Shell’s Common Ingestion Framework (CIF) to add new columns/tables into Databricks, ensuring end-to-end scalable integration from Source to Enriched layers.
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