Tanmoy Maity

Oracle CC&B Techno-Functional Consultant with ~4.5 years of hands-on experience on a large-scale utility implementation for Arizona Public Service (APS). Specialized in the Billing engine and Bill Print Extract — bill, bill segment, and calculation-line processing, extract logic, and BI Publisher / bill PDF generation. Skilled across the OUAF configuration and scripting stack (Business Objects, Maintenance Objects, UI Maps, Zones, Portals, Service/BPA Scripts, Business Services) with strong Java, Groovy, and SQL.

Experienced in production support, root-cause analysis of billing and To-Do exceptions, and delivering accurate, error-free customer bills. 1 full-cycle CC&B implementation experience.

Senior Systems Associate at Infosys Ltd (2022-02 – Present)

Client: Arizona Public Service (APS) | Oracle CC&B Implementation & Support

• Worked extensively on the bill print extract — the logic that pulls bill, bill segment, and calculation-line data from CC&B to produce the extract file feeding BI Publisher for customer bill PDF generation.
• Resolved defects in Java code within the bill extract and implemented new requirements on the Bill Redesign project, ensuring accurate bill data and error-free monthly bill PDFs for X million customers.
• Debugged bill-value discrepancies end to end — validating calculation lines, extract field mappings, and template output — to isolate whether issues originated in billing data or rendering.
• Developed a customer-care support portal for APS using Groovy, Java, HTML, and JavaScript, surfacing customer usage, solar (net-metering), and non-usage data in a single CSR-friendly view.
• Built the portal on the OUAF stack using Service Scripts, Business Objects, Zones, and UI Maps, integrating service-quantity and consumption data for faster high-bill investigation.
• Improved customer-care efficiency and reduced resolution time for high-bill queries by consolidating usage insights into one interface.
• Investigated and resolved CC&B exceptions across billing, meter reads, field activities, and payment errors, using drill-down analysis from source records to root cause.
• Diagnosed systemic vs. isolated issues by grouping errors on shared attributes (bill cycle, rate, route), fixing at source and reprocessing affected populations rather than record-by-record.

[Degree, e.g. B.Tech in Computer Science] – [University / Institute Name] ([Year])