Sareen Shah

• SQL, NiFi, Python, Spark, Impala • Migrating an existing pipeline to another architecture so as to improve the overall efficiency and maintain operational resilience

• SQL, Python, Impala, Spark, Excel, Looker, NiFi, Hadoop, AirFlow • Accomplished ownership and developed the Cardholder Feature Store, consolidating 5000+ cardholder-level features which are extensively leveraged by 5+ cross-functional teams for creating and training models. Successfully expanded its scope globally within 1 year, enhancing project impact across all regions of the world. Incorporated versatile functionalities to enhance scalability and accommodate diverse team requirements. • Significantly optimised efficiency by introducing parallel processing to the NiFi pipeline, resulting in over 70% reduction in execution time. • Developed a product pipeline called 'Small Business Credit Analytics' based on Merchant level data which will equip lenders with instantly accessible data regarding small businesses and help them make lending decisions. • Helped in optimising the product and lowering the runtime of dataset generation by around 33% • Proposed and implemented a solution to reduce the weekly downtime of a data pipeline from 20 hours to a few seconds which translates to almost 99.99% improvement.

• Subjects :- Python, SQL, Excel, Maths, Power BI • Mentoring 30+ students in Data Analytics and Data Science courses by solving their doubts and taking 1:1 sessions.

Lead instructor for Data Analytics batch of Geeksforgeeks in Pune

• SQL, Sisense - Periscope (for creating Dashboards), Excel, AWS Redshift, AWS Athena, Python • Created a policy for Student segment which successfully decreased the DPD 30 risk from 9% to 7.2% while keeping the Approval Rate consistent at around 48% • Implemented and monitored dashboards consisting of various metrics to measure the effect of a new policy for salaried customers applying for the slice card. • Analysed the existing Red Flags and advised on removing some of them by studying their risk and corresponding people in each segment thereby increasing the Approval Rate by around 2%

• SQL, Python, Spark, Alteryx, Tableau, Jenkins, GitLab, AirFlow, Excel, Redshift • Created and deployed Data Quality checks based on business logic, syntactical and semantic attributes. • Developed SQL scripts, framework and orchestration flow for a Patient Data from Alteryx workflows. • Worked on developing scripts, implementing business logic and orchestration of the entire workflow for Sales Data of a product and deploying them in Production • Rated 9 / 10 in Performance Review for overall work