Mahesh Odedra

Project Name: PMI ACM

Project Description: Implemented a global access control model, automating data classification, role-based masking, and governance to secure sensitive client data across multiple regions. Developed metadata-driven policies to enforce scalable and compliant data security frameworks.

• Designed and implemented an enterprise-wide Access Control Model across 51 countries for geo, functional, and other nodes, ensuring compliance and data governance.
• Leveraged Snowflake, Jenkins, Bitbucket, and Atlan to automate access policies and streamline deployment pipelines.
• Utilised metadata-driven frameworks to apply table and column-level tags, enabling fine-grained data classification and governance.
• Implemented dynamic masking policies, ensuring secure, role-based access to confidential client data.
• Strengthened data security, governance, and scalability by integrating metadata management with automated access controls.
• Automated documentation tasks by creating Confluence pages with AI-assisted command summaries, improving knowledge sharing, and saving valuable team time.

Project Name: Digital & Customer Journey (D&C)

Project Description: Establish an automated data warehouse architecture for C&A, incorporating all customer transaction data from initial purchase through to refunds. This process is automated using AWS services and Snowflake as the primary data warehouse platform.

• Streamlined the loading of C&A customer data into Snowflake, reducing data management costs while enhancing visibility into purchase and refund activities.
• Automated batch processing, cutting operational expenses by optimising workflows, reducing manual interventions, and improving data access speed for business teams.
• Delivered AWS S3 infrastructure solutions that significantly reduced cloud storage and compute costs while supporting C&A’s global retail operations.
• Minimized resource consumption and costs by reducing query response times through efficient caching and Snowflake Role implementation, enhancing developer productivity.
• Enabled real-time data updates with Snowpipe, cutting downtime costs and speeding up the resolution of data discrepancies, improving customer service efficiency.
• Managed unstructured data in Snowflake, providing flexible data handling and reducing costs associated with traditional data storage solutions.
• Allocated dedicated Snowflake warehouses for specific workloads, optimizing compute resource usage, reducing processing time, and lowering overall operational costs.

Project Name: SIE_Bluegrass

Project Description: Automate the process of data loading architecture using shell scripting, SnowSQL Logics leveraging AWS Services and Snowflake data warehouse.

• Playing a key role in migrating QLIK application data to Snowflake DW.
• Automate the batch processing with the help of Snowflake Multi-Cluster Warehouses.
• Leverage the Reserved instances to provide complete Infrastructure solutions to Clients including end-to-end configuration using S3 on Linux OS.
• Used snowflake Roles for leveraging the use of caching effectively so that similar queries will be fired on the same warehouse and response time should be quicker for a group of developers.
• Leverage cluster keys to speed up the query performance and compute optimization.
• Automated the loading of files from AWS S3 to snowflake with the help of Snowpipe.
• Additionally having experience loading unstructured data in snowflake.
• Assigned dedicated warehouse to different workloads for cost-saving.

• Playing a key role in design FRB(Factory review Board) Documents and client reviews.
• Worked on analysis of Infrastructure and logical diagrams of multiple move group applications.
• Successfully Migrated DC to DC applications with accuracy and efficiency.

Project Description: Automated the process of on-premise data loading architecture using shell scripting, SQL Logics leveraging AWS Services.

AWS Setup & Architecture:

• Set up a VPC environment & designed an effective backup strategy depending upon client requirements.
• Leverage the Reserved instances to provide complete Infrastructure solutions to Clients including end-to-end configuration using EFS on Linux OS.
• Designed Linux-ready environment architecture to load the Vertica Departmental Warehouse using complex SQL logics and queries.
• Implemented & automated solutions on AWS cloud via Scripting and SQL Logics.
• Deployed the Elastic Load Balancer managed and maintained scalable & highly available systems on AWS using the Auto Scaling feature.
• Employed IAM to create & control AWS users and groups access to AWS services and resources.

• Analyzed & developed scalable, highly available, and fault-tolerant systems on AWS.
• Successfully ported a legacy, on-premises application to AWS and achieved a significant increase in availability.
• Played a key role in selecting appropriate AWS services based on data, compute, database, or security requirements.
• Organized client requirements to define the business strategy to achieve business goals.
• Proactively monitored servers, devices, and applications on cloud watch to identify & rectify potential issues on time while loading data warehouses using SQL logics and queries.

• Implemented and managed continuous delivery systems on AWS from physical infrastructure.
• Implemented & automated solutions on AWS cloud via Jenkins, Scripting, and SQL Logics.
• Designed, managed & maintained tools to automate operational processes to reduce the time from 5 hours to 2 hours by automating solutions to load databases.

• Implemented and managed continuous daily BAU runs on daily, weekly and monthly
  frequencies.
• Implemented Mappings via Informatica 9.1.0 using transformations like Router, Aggregator, Joiner, Expression, Lookup, Update strategy, Sorter, Sequence generator.
• Unit testing & debugging the code and Performance optimization in Informatica 9.1.0 while any failure occurs at the time of loading the data from billing cycles to the database.