Salesforce Data Cloud Engineer

CareCone Group; Sydney; In loco; AUD 140.000 - 190.000; Tempo pieno

Descrizione del lavoro

CareCone Group is seeking a Salesforce Data Cloud Engineer in Sydney, Australia for a permanent role. You will design and implement DMOs/DSOs, map source-to-model layers, and build data offload solutions between Data Cloud and other platforms.

You will also work with Databricks for ingestion/transformation, configure identity resolution, and support end-to-end deployment lifecycles across Dev to Production while coordinating with DevOps and analytics teams.

Competenze

• 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.

Mansioni

• 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.
• Ingestion and transformation of data from multiple source domains into Databricks platform following design principles and data governance standards.
• Build and maintain batch and streaming transform pipelines and workflow orchestration.
• Document data dictionary and cloud object storage design for data offload scenarios.
• Collaborate with DevOps, Data Architects, and operations teams to ensure end-to-end pipeline reliability and observability.
• Demonstrate understanding of how real-time decisioning platforms (e.g. Pega) consume and depend on data outputs.

Conoscenze

Data engineering

Salesforce Data Cloud

Databricks

SQL

Python

Release governance

Documentation

Strumenti

Databricks

Pega

SQL tooling

Descrizione del lavoro

Role : Salesforce Data Cloud Engineer

Type of role - Permanent Position

Location : Sydney, Australia

Key Responsibilities

Salesforce Data Cloud

• 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.

Decisioning Platform (Pega or equivalent)

• 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.

Skills & Experience

Essential

• 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.