Sourav Banerjee

• Planned various product configurations to meet diverse customer needs.
• Defined strategies for migrating existing workloads into the cloud environment.
• Documented account activities and generated sales reports.
• Resolved complex system issues related to multi-cloud deployments in production environments.
• Optimized costs by right-sizing resources based on current usage trends in the cloud environment.
• Collaborated with sales team to understand customer requirements, boost product sales and provide sales support.
• Assisted customers with troubleshooting issues related to their applications running on public clouds.
• Assisted account executives with prospect evaluation and qualification.
• Researched and implemented new technology platforms to support development initiatives.
• Developed cloud-based solutions using AWS, Azure, and Google Cloud Platform technologies.
• Worked with cross-functional teams to achieve goals.
• Utilized advanced technical skills and expertise to troubleshoot complex problems and implement solutions.

• Lead open-source contributor for Overwatch, Databricks' own Observability Tool, with $2.2M ARR.
• Performed advanced analytics on structured and unstructured data using SQL, Python, R.
• Optimized existing queries to improve query performance, and reduce the load on the server.
• Deployed machine learning models to the production environment for real-time predictions.
• Built complex reports utilizing multiple sources of information from different systems.
• Designed, built, and maintained high-performance databases for reporting and analysis purposes.
• Created ETL scripts to move and transform data from various sources into a centralized repository.
• Implemented new database technologies, such as NoSQL databases, to store large volumes of data efficiently.
• Automated manual processes by creating custom scripts and programs using scripting languages like Bash, PowerShell.
• Cleaned and manipulated raw data.
• Exceeded customer satisfaction by finding creative solutions to problems.
• Collaborated closely with team members to achieve project objectives and meet deadlines.
• Developed tools and applications for monitoring data quality and integrity across all applications and databases.

• Provided technical support to business users on using Big Data tools for their analytical needs.
• Integrated existing systems with new platforms such as AWS S3 or Azure Blob Storage.
• Developed new functions and applications to conduct analyses.
• Cleaned and manipulated raw data.
• Developed ETL jobs to extract, transform, and load data from various sources into the target system.
• Recommended data analysis tools to address business issues.

• Developed Kafka Streaming Pipeline for data ingestion from Oracle Database to Cassandra.
• Engineered PySpark and Scala-Spark jobs for transforming data into required formats.
• Configured EMR cluster and AWS Lambda function for job scheduling and deployment.
• Created Azure Data Factory Pipeline for efficient data ingestion and processing.
• Led cross-functional teams in systems integration projects to enhance collaboration.
• Executed debugging and automation scripts using Python to improve efficiency.
• Created MongoDB collections for effective data management and ingestion.
• Communicated with clients to gather requirements for accurate implementation.

• Developed and maintained scalable software applications for various platforms.
• Optimized existing software systems for improved performance and scalability.
• Developing Big Data Platform using Stg -> Trans -> Hub Layered Architecture on Supply Chain
• Documented software designs and architecture for future reference and maintenance.
• Implemented robust code in multiple programming languages, including C++ and Python.
• Coordinated with quality assurance teams to ensure software met all testing criteria.
• Creating a data repository that will help in machine learning and reporting purposes.
• Acted as a team member, working on automating the end-to-end process of the data lifecycle across the layered architecture.
• Preparing the model for the classification problem, including data gathering, cleaning, validation, quality checks, exploratory data analysis, and missing value and outlier treatment.
• Performing data pre-processing using NLTK (Natural Language Toolkit).

· Contributing in requirement analysis and solution discussion

· Analyzed log data from different sockets & files and provided insights about the risk associated with the user

· Developed Hive scripts for end user / analyst requirements to perform ad hoc analysis

· Solved performance issues in Hive with understanding of Joins, Group and aggregation and how does it translate to Map Reduce jobs.

· Developed simple to complex Spark jobs using Scala; contributed in the requirement and analysis phase

· Managed the importing of data from various data sources; performed transformations using Spark, Hive & Map Reduce

· Engaged in collecting the data from different data sources using SQOOP

· Migrated Map Reduce jobs to Spark

· Wrote Hive queries to analyses data in Hive Warehouse using Hive Query Language (HQL)

· Developed Hive and Spark SQL for the business logic

· Transformed structured data using Dataframe and HiveQL