Senior Salesforce Data Cloud Developer
New
J
JobgetherInformation Technology
BrazilFull-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- SQLETLRESTful APIsData modelingGenerative AI
Requirements
- Solid professional experience working with Salesforce Data Cloud and its core capabilities.
- Strong knowledge of Data Streams, Data Model Objects (DMOs), Identity Resolution, Unified Individual, Calculated Insights, and audience segmentation.
- Experience with data modeling, data architecture, and integration across multiple platforms.
- Proficiency in SQL for data analysis, transformation, and validation.
- Hands-on experience with APIs, ETL/ELT processes, and enterprise system integrations.
- Strong understanding of the Salesforce ecosystem and integrations between Data Cloud and other Salesforce Clouds.
- Experience with data governance, quality, security, privacy, and lifecycle management.
- Knowledge of semantic-layer modeling to support analytics and AI applications.
- Experience configuring indexes, context-retrieval strategies, and data foundations for generative AI applications.
- Understanding of distributed data architectures, including Bring Your Own Data Lake (BYODL) scenarios.
- Ability to act as a technical leader and collaborate effectively with multidisciplinary teams.
Responsibilities
- Design, implement, and continuously evolve scalable solutions using Salesforce Data Cloud.
- Define data modeling, ingestion, unification, identity resolution, and relationship strategies across multiple data sources.
- Configure and manage Data Streams, Data Model Objects (DMOs), Identity Resolution, Unified Individual, Calculated Insights, and audience segmentation.
- Ensure data quality, governance, security, privacy, and traceability throughout the data lifecycle.
- Integrate Data Cloud with Salesforce products, enterprise systems, APIs, and external platforms using appropriate ETL/ELT approaches.
- Enable audience activation, personalized journeys, analytics, and other data-driven business use cases.
- Build and support integrations between Data Cloud and AI solutions for personalization, recommendations, generative AI, and intelligent-agent use cases.
- Partner with architects, data engineers, CRM teams, and business stakeholders to define and evolve technical solutions.
- Monitor implementation performance, data volumes, costs, and operational efficiency, identifying opportunities for optimization.
- Act as a technical reference for the team, promoting best practices, knowledge sharing, and continuous improvement.
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