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Data Engineer (Salesforce Data Cloud + AWS + Databricks + Pega Decisioning)CareCone Group · Sydney, New South Wales, Australia
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CareCone Group

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Data Engineer (Salesforce Data Cloud + AWS + Databricks + Pega Decisioning)

🗓️ Posted 2026-09-14 Sydney, New South Wales, Australia Full-time Hybrid ICT
💰 Salary Not shared 📊 Market A$8,333–A$12,500/mo

About the Company

We are seeking a skilled Data Engineer to work across Salesforce Data Cloud and Databricks

Responsibilities

  • ● Build and manage DMOs, DSOs, and source to model mappings.
  • ● Develop data integration and offload solutions with upstream/downstream systems.
  • ● Configure Identity Resolution rules and unified customer profiles.
  • ● Support deployments across Dev, SIT, UAT, Pre Prod, and Production environments.
  • ● Manage data onboarding, validation, attribute mapping, and documentation.
  • ● Design and maintain batch and streaming data pipelines.
  • ● Ingest and transform data from CRM, digital, and third party sources.
  • ● Support data dictionary creation and cloud storage based data offloads.
  • ● Collaborate with DevOps, Architects, and Operations teams to ensure platform reliability.
  • ● Support data requirements for real time decisioning and personalization platforms.
  • ● Partner with analytics and decisioning teams to ensure timely, accurate data delivery.
  • ● Contribute to solution planning and dependency management for decisioning use cases.
  • ● Deliver multiple use cases in Agile squads while managing cross team dependencies.
  • ● Create and maintain technical documentation, implementation plans, and runbooks.
  • ● Participate in sprint ceremonies, backlog refinement, and release activities.
  • ● Provide SIT, UAT, and data validation support across environments.

Requirements

  • ● 5 years of enterprise data engineering experience.
  • ● Hands on experience with Salesforce Data Cloud (DMOs, DSOs, Data Streams, Identity Resolution).
  • ● Strong knowledge of Databricks, data lakes, ETL/ELT, and pipeline orchestration.
  • ● Proficiency in SQL and Python.
  • ● Experience with release management, deployment processes, and technical documentation.
  • ● Knowledge of Pega or other real time decisioning platforms.
  • ● Experience with AWS S3, Azure Data Lake, and workflow orchestration tools (Airflow or equivalent).
  • ● Understanding of data governance, lineage, and quality frameworks.
  • ● Exposure to MarTech, large scale transformation programs, and Agile/SAFe delivery models