Mohit Kanti

• Implemented robust data processing and transformation pipelines using Spark on AWS S3, achieving significant enhancements in retail data analytics efficiency. This led to a 30% improvement in inventory planning accuracy and a 25% faster data processing time. • Engineered and managed comprehensive ETL workflows and data pipelines, incorporating Airflow for dynamic scheduling and real-time integration. This automation resulted in a 40% reduction in manual data handling and a 20% increase in data pipeline reliability. • Optimized Hive queries and data partitioning strategies on top of S3, significantly improving data retrieval speeds by 35% and enhancing join performance on Hive tables, leading to a 20% increase in overall query efficiency. • Developed and deployed RESTful APIs using Flask and Spring Boot, facilitating seamless system integrations. This initiative boosted data interchange capabilities by 50% and enhanced system interoperability. • Spearheaded the automation of data processing tasks through the creation of Java and Python scripts, leading to a 60% reduction in manual effort and a 30% increase in process efficiency. • Achieved a 40% improvement in Spark job performance through strategic partitioning, bucketing, and memory management, enhancing the execution speed and reducing resource consumption. •Played a key role in sprint planning and Agile Scrum meetings, driving the productivity of scrum sessions up by 30% and enhancing project delivery timelines by 20%. • Led the development of end-to-end data pipelines using Spark, culminating in the seamless integration of processed data into Snowflake data warehouse solutions. This effort streamlined analytics workflows, resulting in 50% increase in data accessibility for the data science team. • Implemented Kafka Connects for diverse data sources and sinks (AWS S3, Salesforce, Splunk, HDFS), optimizing data ingestion and export processes, which improved data flow efficiency by 40% and reduced latency by 25%.

• Executed comprehensive data analytics on AWS S3 using Spark, leading to a 45% improvement in data processing efficiency and a 30% increase in analytics accuracy. • Leveraged Java and Python libraries (Pandas, NumPy) for advanced data manipulation, analysis, and visualization, enhancing decision-making speed for strategic initiatives by 20%. • Identified and resolved data quality issues through profiling and cleansing, increasing data accuracy and reliability by 25%. • Designed and executed ETL processes with Java and Python, streamlining data integration and reducing discrepancies by 40%. • Integrated Apache Kafka with HDFS and S3 pipelines, optimizing Hive jobs and achieving a 35% performance increase in data processing and reporting. • Engineered efficient ETL processes using Spark for Snowflake data warehouse, enhancing data storage solutions and accessibility by 50%. • Developed Hive schemas and data models, both normalized and denormalized, enhancing data model efficiency and query performance by 30%. • Implemented a comprehensive data lake strategy, improving data availability and governance, leading to a 40% improvement in data access and analysis efficiency. • Automated and optimized data flow pipelines, improving operational efficiency, reducing manual intervention by 20%, and increasing workflow efficiency by 50%. • Collaborated closely with the Data Science team to optimize Hive tables on HDFS, improving data preparation speed and accessibility for analytics by 25%. • Developed and maintained robust CI/CD pipelines using Jenkins, increasing deployment frequency by 50% and reducing production rollbacks by 35%, enhancing product quality.

• Created and maintained interactive dashboards in Tableau, enabling stakeholders to easily monitor key performance indicators (KPIs) and make data-driven decisions. • Produce detailed mapping spreadsheets, enhancing data transformation efficiency for the ETL team by 30%. • Conduct in-depth data analysis using SQL scripts, improving data quality and accuracy during loads and extracts by 20%. • Oversaw extensive dataset management, resulting in a 25% improvement in analytical efficiency and crafted compelling visualizations using Tableau enhancing data presentation. • Designed dynamic business solutions and dashboards using Excel, Power Pivot, DAX, and Power Query, contributing to a 15% increase in data-driven decision-making efficiency.