Experience
2024 — Now
New Jersey, United States
2023 — 2024
2023 — 2024
• Collaborated closely with co-mentors while utilizing business intelligence reporting tools like Tableau to derive actionable insights and achieve informed decision-making process.
• Designed relational database management systems (RDBMS) tables, views, indexes, stored procedures, cursors, triggers, performing advanced data modeling. Additionally, optimizing existing queries to enhance efficiency.
• Actively participated in TVP meetings and dealt with data from surveys and events to create analytical dashboards.
• Empowered stakeholders enabling accelerated data interpretation by 40% and further extract valuable insights quickly as
compared to traditional processes, implementing detailed analytical dashboards.
• Worked in collaboration with a senior mentor and conducted weekly meetings with the mentee, fostering discussions
around academic progress and addressing any challenges they may encounter along their journey.
2022 — 2023
Boston, Massachusetts, United States
• Designed and implemented scalable big data architectures tailored to business needs, balancing performance
requirements with considerations for data volume, velocity, and variety.
• Applied in-depth Extract, Transform, Load (ETL) skills to orchestrate the smooth movement of data, optimizing
processes for efficiency and maintaining data integrity throughout.
• Applied expertise in data modeling to design structures that optimize storage, retrieval, and processing, catering to the
unique challenges posed by varying data volumes and complexities.
• Demonstrated proficiency in setting up and maintaining Hadoop clusters, ensuring robust distributed storage and
efficient processing of vast datasets.
• Developed and optimized notebooks in Azure Data bricks, showcasing the ability to translate complex data
engineering tasks into clear and efficient code for streamlined analysis and processing.
• Successfully orchestrated and scheduled jobs within Azure Data bricks, ensuring the efficient execution of data
processing tasks and maximizing the platform's capabilities for scalable and reliable data solutions.
• Demonstrated expertise in crafting innovative Spark applications, utilizing advanced programming skills to tackle
complex data processing and analytics challenges.
• Possesses a deep understanding of Spark's architecture, allowing for the design and implementation of highly
optimized and scalable data transformation processes.
• Proven track record in writing and optimizing Spark code for peak performance, ensuring efficient data processing and
analysis while meeting stringent performance benchmarks.
• Tech Stack: Python, Spark ecosystem, Databricks, Hadoop ecosystem, HDFS, MYSQL, Redshift, ETL, Linux, S3, AWS,
Data Modeling, Azure data factory, ADLS Gen2.
2018 — 2021
2018 — 2021
India
• Reduced time required to make stocking decisions by 25%, programming an efficient tool using SQL and Snowflake.
• Generated data extraction pipelines and further leveraged advanced MS Excel techniques (VLOOKUPS and Pivot Tables)
to develop customer dependent monthly inventory analysis reports for 22 fulfillment centers for accurate stocking
decisions.
• Empowered stakeholders enabling accelerated data interpretation by 40% and further extract valuable insights quickly
as compared to traditional processes, implementing detailed PowerBI dashboards.
• Improved customer demographic analysis by 30% to improvise business decisions, employing effective python scripts
to integrate 4 critical attributes from Census data into transactional data warehouse.
• Enhanced SKU demand planning for 70 customers, analyzing Key Performing Indicators (KPIs) for order data.
• Collaborated with cross-functional teams, including operations and finance, to align inventory management strategies
with the company's financial goals, resulting in a 5% decrease in carrying costs.
• Implemented data quality checks and validation processes to ensure the accuracy and reliability of data used in decisionmaking, reducing data errors by 18%.
• Applied time series analysis to identify seasonality patterns and trends in demand, allowing for more accurate inventory
replenishment strategies.
• Created interactive data dashboards and reports in Power BI to provide stakeholders with real-time insights into supply
chain performance, enabling more informed decision-making.
• Created interactive data dashboards and reports in Power BI to provide stakeholders with real-time insights into supply
chain performance, enabling more informed decision-making.
Education
Northeastern University
Master of Science - MS
2021 — 2023
Savitribai Phule Pune University
Bachelor of Science - BS
2016 — 2020