• Databricks ETL Optimization and Revamping of an existing Dashboard which helped stakeholders to get visibility on conversion rate across various dimensions related to Educational Institutes and other demographics.• Modified existing ETL to include new features as part of Annual OKRs and performed backfilling of data across different time intervals.• Ingested Raw data sent by partners into Redshift table through Databricks ETL as a part of Quarterly finance report.• Debugged ETL’s to find the Root cause of the issue and modifying it according to the Business requirements.

• Implemented Association rule mining for frequent itemsets being brought together for top 1000 variants and used past three months transaction data to train incrementally and deploy the model on GCP using Google Cloud Scheduler,Cloud Functions,Topics and FP Growth Algorithm and visualizing the output on Tableau which was used to better design Combos of products.• Automated fetching of top line metrics data from dashboards using python script and sending those sheets to key stakeholders on a regular basis using TableauServerClient,Python,Automated mailing,Google Cloud Scheduler which helped to reduce the TAT for spooling data from tableau manually.• Worked on a number of Root Cause Analysis thereby highlighting major in-app issues and contributed to data driven decisions by performing A/B Experiments related to Delivery fee optimization, Cart weight limit, Clicks on offer banners, Multipacks and Combos.• Built complex logic of new filters and features to integrate into existing dashboards related to fraud, misuse and delivery options.• Validated fact tables related to User’s data built by the Data Engineering team by writing sql queries covering major edge cases for simulating various checks like smell check, null value check and deduplication checks and highlighted a couple of issues related to selection of grain for the fact tables and discounts data mismatch.

• Worked for a Renowned Telecommunication client, wherein we owned the entire data life cycle for data fetched through an internal portal by their stakeholders.• Developing Logic for stored PLSQL packages for New Data Reports and Analyzing issues in code logic of stored packages which are triggered when user tries to fetches data on the web portals.• Monitoring daily deliveries to be sent using SFTP and Modifying bash scripts according to amendments in the deliverables.• Handling data requirements by different stakeholders.