Salesforce Data Cloud Engineer – Audience & Activation

This is a hands-on data engineering role focused on building scalable audience, segmentation, and activation capabilities within Salesforce Data Cloud.
You will transform complex data into actionable customer insights that support personalized engagement and data-driven decision-making.
The role combines data architecture, SQL development, cloud integrations, real-time processing, and strong data governance practices.
You will design and optimize data solutions that connect multiple platforms while maintaining high standards of quality, accuracy, and reliability.
The position offers the opportunity to work with technologies spanning Salesforce Data Cloud, Snowflake, AWS, Azure, and GCP.
You will play a key role in enabling sophisticated audience targeting and ensuring data is structured for analytics and activation.
This is an ideal opportunity for a technically strong data professional who enjoys solving complex integration challenges and translating business requirements into robust solutions.

• 4+ years of professional experience in data engineering, cloud architecture, or a related technical discipline.
• Proven hands-on expertise with Salesforce Data Cloud, including Data 360 and its core components.
• Strong proficiency in SQL, with the ability to manipulate, analyze, transform, and report on complex datasets.
• Practical experience with cloud and data platforms such as Snowflake, AWS, Azure, or Google Cloud Platform (GCP).
• Demonstrated experience configuring and managing Data Extensions and Data Model Objects (DMOs).
• Strong understanding of data quality principles, data integrity, troubleshooting techniques, and governance standards.
• Hands-on experience with Calculated Insights and Computed Traits for developing meaningful audience and business intelligence capabilities.
• Knowledge of consent management, data privacy practices, and relevant regulatory requirements.
• Familiarity with Data Streams, real-time ingestion, and continuous data processing architectures.
• Strong data architecture and integration skills, with the ability to connect disparate platforms and source systems effectively.
• Ability to understand complex business requirements and translate them into practical, scalable technical solutions.
• Strong analytical and problem-solving skills, with a detail-oriented approach to data accuracy and system reliability.
• Effective communication and collaboration skills for working with technical and business stakeholders.