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XPT Software Australia Pty Ltd

Data Engineer – Salesforce Data Cloud

XPT Software Australia Pty Ltd Sydney, New South Wales, Australia

IT Services and IT Consulting · 51-200 employees

3 d ago
data-engineer Principal (10+ yrs) Contractor Australia
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About the role

Design and build data model objects and mapping layers within Salesforce Data Cloud while managing data offload solutions. Govern data onboarding processes and support deployments across various environments including SIT, UAT, and production.

What they look for

Salesforce Data Cloud Data Engineering DMO DSO Identity Resolution Databricks Data Lake SQL Python Pipeline Orchestration Change Management Technical Documentation Data Ingestion Data Governance Release Management

Requirements

Requires 8-12 years of experience with a strong background in Salesforce Data Cloud and data engineering. Proficiency in SQL, Python, and experience with Databricks or similar data lake environments is essential.

Full description

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.

Essential Skills

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.

Highly Desirable

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