
Worked on the navikt/crm-platform-integration and navikt/crm-nks-base repositories, focusing on enhancing data accuracy and maintainability in Salesforce environments. Delivered support for fractional employee counts by updating the antallAnsatte field from Integer to Decimal, adapting the data model, handler logic, and tests to ensure precise downstream reporting. Improved code clarity by refining documentation and comments around address merging logic without altering functionality. Addressed a bug in the TAG_Log_Call_in_Account Salesforce Flow, ensuring tasks are assigned the correct record type for reliable CRM analytics. Utilized Apex, XML, and Salesforce Flow, emphasizing data type handling and robust integration practices throughout the work.
For 2025-04, the work focused on stabilizing CRM data integrity and ensuring reliability in the Account flow within navikt/crm-nks-base. A targeted bug fix was implemented to ensure Task records created in the TAG_Log_Call_in_Account flow are assigned the correct record type, preventing miscategorized tasks and improving downstream analytics.
For 2025-04, the work focused on stabilizing CRM data integrity and ensuring reliability in the Account flow within navikt/crm-nks-base. A targeted bug fix was implemented to ensure Task records created in the TAG_Log_Call_in_Account flow are assigned the correct record type, preventing miscategorized tasks and improving downstream analytics.
December 2024: Delivered fractional employee counts support in navikt/crm-platform-integration, updated data model and tests; clarified address merging logic in Salesforce integration, improving maintainability. Resulting data accuracy supports downstream reporting, analytics, and cross-system consistency; focused on business value and data quality while maintaining code health.
December 2024: Delivered fractional employee counts support in navikt/crm-platform-integration, updated data model and tests; clarified address merging logic in Salesforce integration, improving maintainability. Resulting data accuracy supports downstream reporting, analytics, and cross-system consistency; focused on business value and data quality while maintaining code health.

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