Arunprasath Varatharaj

Client : STANDARD CHARTERED BANK

Project: ANTI MONEY LAUNDERING (Monitoring & Compliance)

• Identified issues within databases, performed troubleshooting and implemented effective solutions.
• Reduced server downtime by proactively monitoring system performance and addressing potential issues before they escalated.
• Ensured accurate reporting results with thorough validation of ETL/ELT processes, data transformations, and aggregations.
• Streamlined deployment processes through the use of Azure DevOps CI/CD ETL/ELT pipelines, reducing time to production and increasing efficiency.
• Achieved faster development cycles using Agile methodologies, including Scrum or Kanban processes.
• Experienced in designing and maintaining data pipelines using ODI, Autosys, and Oracle-based ETL workflows supporting large-scale financial data systems.

Client : E-ZPASS NJ (New jersey)

Project: Electronic toll collection systems

• Designed and executed comprehensive test plans to validate the functionality, reliability, and performance of new databases before deployment.
• Reduced system downtime, proactively monitoring databases and addressing potential issues before they escalated.
• Collaborated on ETL (Extract, Transform, Load) tasks, maintaining data integrity and verifying pipeline stability.

Client : BOTW (BANK OF THE WEST)

Project: CORP FUNCTION

• Mentored junior support engineers, fostering a positive learning environment and promoting professional growth.
• Contributed to business development initiatives by identifying opportunities for upselling or cross-selling products based on clients'' needs.

Client : IBL (IDFC FIRST BANK)

Project: RETAIL BANKING (LOANS)

• Analyzed existing SQL queries to identify opportunities for improvements.
• Developed efficient stored procedures for complex business logic, reducing processing time and improving system stability.
• Enhanced database performance by optimizing SQL queries and indexing strategies.

Client : CITI BANK INDIA

Project: RETAIL BANKING (LOANS)

• Improved decision-making capabilities by developing comprehensive data models that captured relevant business information.
• Streamlined database performance by optimizing SQL queries and implementing indexing strategies.
• Provided excellent customer support during implementation phases, addressing concerns promptly and proactively anticipating potential issues.