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Responsibilities
- Design and build Data Model Objects (DMOs), Data Stream Objects (DSOs), and source-to-model mapping layers within Salesforce Data Cloud.
- Develop and maintain data offload solutions between the Data Cloud and upstream or downstream platforms.
- Configure and validate Identity Resolution (IR) rulesets and unified contact profiles within the Data Cloud environment.
- Support deployments across development, SIT, UAT, pre-production, and production environments, including preparation of implementation plans, change management documentation, and post-go-live validation.
- Manage and govern data onboarding processes including data dictionaries, attribute mapping reviews, and build validation.
Requirements
- 3–5+ years of hands-on data engineering experience in a complex enterprise environment.
- Demonstrated experience with Salesforce Data Cloud, including DMO/DSO development, data ingestion, identity resolution, and end-to-end deployment lifecycle management.
- Strong working knowledge of Databricks, data lake, or similar UDP environment, including batch and streaming ingestion patterns and pipeline orchestration.
- Proficiency in SQL and at least one scripting language (Python preferred) for data transformation and pipeline development.
- Experience working across multiple delivery environments (Dev / SIT / UAT / Pre-Production / Production) with formal change management and release governance processes.
- Ability to write clear technical documentation, including implementation plans, data dictionaries, and solution design notes.
Skills
- Salesforce Data Cloud
- Data Model Objects (DMOs)
- Data Stream Objects (DSOs)
- Identity Resolution (IR)
- Databricks
- Data Lake
- SQL
- Python
- Technical Documentation
Experience Level
- 3-5+ years