> Markdown version of [/jobs/ext/4444984-salesforce-data-cloud-developer](https://www.wearedevelopers.com/jobs/ext/4444984-salesforce-data-cloud-developer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Salesforce Data cloud developer - **Company:** Texnere Americas Inc - **Location:** United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Cloud Engineering, Extract Transform Load (ETL), Data Transformation, Cloud Services, Salesforce.Com, SQL Databases, Data Streaming, Data Ingestion, SOAPAPI, Salesforce Sales Cloud, Data Lakes, Integration Frameworks, Restful APIs, Data Pipelines, Marketing Cloud, User Identification, Mulesoft - **Published:** October 26, 2026 - **Apply:** https://www.dice.com/job-detail/97f4d0fa-fec4-444d-a64f-a8816d8aeeaa ## About the Role · 4-6 years of Salesforce experience with strong hands-on Salesforce Data Cloud expertise. · Strong knowledge of Data Cloud architecture, data modeling, identity resolution, and segmentation. · Experience with Salesforce APIs, MuleSoft/integration tools, SQL, and data transformation. · Strong proficiency in SQL, data transformation concepts, and REST/SOAP APIs · Deep familiarity with Sales Cloud, Marketing Cloud, Service Cloud, and data privacy/compliance standards · Salesforce Data Cloud certified ## Description · Design and implement Salesforce Data Cloud solutions and data models. · Configure Data Streams, Data Lake Objects (DLOs), Data Model Objects (DMOs), and Identity Resolution. · Integration & Ingestion: Manage data pipelines using APIs, ETL tools, orMuleSoft to connect external data sources · Develop and manage data ingestion and integration using APIs, MuleSoft, and other ETL tools. · Configure Calculated Insights, Segmentation, and Data Actions. · Work with stakeholders to understand business requirements and translate them into scalable Data Cloud solutions. · Troubleshoot data quality, integration, and performance issues.