Adarsh S Moni

Data Engineer, Analytics Team Lead
Skit.ai
Feb 2024 – Present

• Lead the Analytics team in designing and implementing scalable data solutions to support business intelligence and reporting needs.
• Architected and deployed a data lake using AWS S3, parquet, and iceberg tables, enabling flexible and efficient data storage and retrieval.
• Spearheaded the migration of analytics workloads from PostgreSQL(OLTP) to Amazon Redshift, significantly improving query performance and scalability.
• Decoupled Analytics efficiently from Live systems and migrated more than billion record's worth of conversational data to OLTP
  Developed an on-demand PII data purging tool, ensuring compliance with data privacy regulations and reducing manual intervention.
• Optimized dashboards and reporting pipelines, resulting in faster insights and improved decision-making for stakeholders.
• Established best practices for query engine flexibility, supporting diverse analytics use cases across the organization.
  

Solutions Engineer
Skit.ai
Aug 2022 – Jan 2024

• Designed and deployed custom data solutions for enterprise clients, focusing on automation and integration of conversational AI analytics. Developed RESTful APIs and microservices to support data ingestion, transformation, and reporting.
• Worked closely with product and engineering teams to translate business requirements into technical specifications.
  Enhanced data infrastructure to improve scalability, reliability, and performance.
• Optimized data processing by implementing efficient ETL pipelines and streamlining database design.

• Worked on Financial Record to Report Tool as part of Cognitive Process Team.
• Responsibilities:
• Maintaining Process and code related to Financial Onboarding Functionality.
• Enhancement of Onboarding functionality by creating required APIs and writing code to create dynamic spaces in different databases and creating containers directly via code.
• Used Celery to execute distributed task related functionalities.

• Digital Transformation is an internal project of Mphasis.
• Worked towards building a micro-service for internal project governance(iPG) using python flask restx and mongo DB.
• Flask Framework is used for creating APIs in Pycharm IDE
• Responsibilities:
• Implementation of the Restful APIs as per the requirements.
• Unit Testing to check the functionality and verify the results and Bug fixes if any.
• Database Designing
• Inbuilt Application scheduler using apscheduler library
• Creating modules to upload excel sheets and perform metric computations related to each project
• Bug Fixes if any
• Achievements:
• Appreciation from Vice President of Mphasis for automating metric calculations using upload features for gathering project data numbers and contract to compute metric data and status of projects.

• AIG W2k8 Remediation is Deployment project where multiple legacy applications with servers whose support got expired from microsoft were redeployed by modernizing these applications and virtually hosting them in citrix servers.
• Responsibilities:
• Analysis of Legacy Applications written in legacy technologies.
• Changes in code to accomodate structural change in deployment while retaining same functionality.
• Server configuration changes.