- Design and build Data Model Objects (DMOs), Data Stream Objects (DSOs), and source-to-model mapping layers within Salesforce Data Cloud (SFDC360).
- 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.
Databricks (Unified Data Platform)
Demonstrate a sound understanding of:
- Ingestion and transformation of data from multiple source domains (e.g. CRM feeds, third-party data, digital signals) into the platform following approved design principles and data governance standards.
- Building and maintaining batch and streaming transform pipelines and workflow orchestration.
- Data dictionary documentation and cloud object storage design for data offload scenarios.
- Collaboration with extended team like DevOps, Data Architects, and operations teams to ensure end-to-end pipeline reliability and observability.
- Demonstrate a sound understanding of how real-time decisioning platforms (such as Pega) consume and depend on data engineering outputs.
- Work with decisioning and analytics teams to ensure accurate and timely data availability for personalisation and customer engagement use cases.
- Participate in cross-team planning and technical reviews as they relate to data dependencies for decisioning workflows.
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Skills & Experience
- 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 - implementation plans, data dictionaries, and solution design notes.
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Salesforce Data Cloud Engineer in Sydney employer: CareCone Group
CareCone Group is an exceptional employer located in the vibrant city of Sydney, offering a dynamic work culture that fosters innovation and collaboration. Employees benefit from ongoing professional development opportunities, competitive remuneration, and a supportive environment that values work-life balance. Joining our team means being part of a forward-thinking organisation dedicated to delivering high-quality IT solutions while ensuring compliance with Australian working rights.
