Salesforce Data 360 (Data Cloud) Engineer

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Visit us at www.accenture.com About The Salesforce Business Group Accenture's Salesforce Business Group is the part of Accenture Technology devoted to selling, delivering, and supporting Salesforce technology-based projects across Australia & New Zealand. Part of our global practice, our local and international ability is recognised unanimously as number 1 by Industry Analysts in their annual ratings on Salesforce consulting partners. We think we're unique among our peers with our ability to understand Salesforce, its ecosystem and the career goals of those working in the Ohana. We also bring our collective Accenture capability to our Salesforce work. We work with our industry, consulting, strategy, service design and digital consultants to transform our clients. About The Role We are seeking a highly skilled Salesforce Data Cloud Engineer to design, implement, and optimise scalable data solutions within Salesforce Data 360 (formerly Salesforce Data Cloud). You will be responsible for integrating diverse data sources, configuring data models, orchestrating data flows, and enabling real-time, actionable insights for business stakeholders. This role requires a blend of engineering discipline, data management expertise, and deep knowledge of Salesforce’s data architecture. Key Responsibilities Design and implement Data 360 data models, including Data Streams, Data Bundles, Data Lake Objects (DLOs), and Data Model Objects (DMOs). Build and maintain data transformations, including Data Mapper recipes, identity resolution rules, and calculated insights. Create scalable segmentation, activation, and unification pipelines to support personalisation and analytics use cases. Develop and manage ETL/ELT pipelines into Data 360 using connectors such as MuleSoft, Marketing Cloud, AWS, Azure, APIs, and flat-file ingestion. Optimise data ingestion performance with monitoring, validation, and exception handling processes. Implement real-time and batch data synchronisation across enterprise systems and Salesforce clouds. Define and enforce data governance, including data retention rules, lineage, cataloguing, and compliance policies. Ensure data security and privacy align with organisational and regulatory standards (GDPR, CCPA, HIPAA as applicable). Develop automated data quality monitoring, troubleshooting, and optimisation processes to ensure reliable, trusted data for Agentforce and other AI capabilities. Work closely with CRM, Marketing, Analytics, Product, and Data Science teams to translate business requirements into technical designs. Partner with Salesforce Administrators, Developers, and Architects to ensure cohesive multi-cloud solutions (Sales, Service, Marketing, Commerce, etc.). Create technical documentation, data dictionaries, and reference architecture diagrams. Establish best practices for Data Cloud usage, performance tuning, monitoring, and lifecycle management. Required Qualifications Bachelor’s degree in Computer Science, Information Systems, Engineering, or equivalent experience. 5+ years of experience working with Salesforce, with at least 1+ year in Salesforce Data 360 (or equivalent CDP experience). Strong understanding of: Data modeling and data architecture principles ETL/ELT pipelines and data integration patterns Identity resolution, deduplication, and unification logic SQL, JSON, REST/SOAP APIs Hands-on experience with Salesforce Data 360 features including Data Streams, DLOs/DMOs, Calculated Insights, Segments, and Activation Targets. Desirable Qualifications Salesforce certifications such as: Certified Data Cloud Consultant Salesforce Administrator, Platform App Builder, Platform Developer I MuleSoft or Marketing Cloud certifications Experience with: Agentforce flows, actions, topics, and secure data access patterns Cloud platforms (AWS, Snowflake, GCP, Azure) Streaming technologies (Kafka, Kinesis) Python, Spark, or similar data engineering tools Background in marketing automation, customer analytics, or enterprise data platforms. Soft Skills Strong analytical problem-solving abilities. Excellent communication skills, able to convey technical concepts to non-technical audiences. Ability to work independently in a fast-paced, agile environment. Detail-oriented with a passion for data accuracy and reliability.