Salesforce Data Cloud Engineer – Audience & Activation
Summary
Remote (India) Salesforce Data Cloud engineer role focused on audience segmentation and activation: the engineer designs Calculated Insights, Computed Traits, SQL-driven data flows, Data Streams, DMOs, and Data Extensions in Salesforce Data Cloud (Data 360), supported by cloud platforms like Snowflake, AWS, Azure, or GCP, serving IT-services clients.
Salesforce Data Cloud Engineer – Audience & Activation
Summary
Responsibilities
- Design, implement, and optimize Calculated Insights and Computed Traits to enhance audience segmentation and targeting capabilities.
- Develop and manage complex SQL queries to extract, transform, and load data efficiently within the Salesforce ecosystem.
- Configure and maintain Data Extensions to support scalable data storage and retrieval operations.
- Architect data pipelines and integrations utilizing cloud infrastructure such as Snowflake, AWS, Azure, or GCP.
- Conduct thorough data quality assessments and troubleshooting to resolve discrepancies and ensure data integrity.
- Establish and enforce Consent management protocols and Data Governance frameworks to maintain regulatory compliance.
- Manage the configuration of Salesforce Data Cloud (Data 360) to support real-time data ingestion and processing.
- Implement and monitor Data Streams to facilitate continuous data flow between source systems and the data cloud.
- Define and maintain Data Model Objects (DMOs) to structure data relationships and support advanced analytics.
Requirements
- Minimum of 4+ years of professional experience in data engineering, cloud architecture, or related technical fields.
- Proven expertise in Salesforce Data Cloud, specifically regarding Data 360 and its core components.
- Strong proficiency in SQL for data manipulation, analysis, and reporting.
- Hands-on experience with cloud platforms including Snowflake, AWS, Azure, or Google Cloud Platform (GCP).
- Demonstrated ability to manage Data Extensions and Data Model Objects (DMOs) effectively.
- Deep understanding of data quality principles, troubleshooting methodologies, and governance standards.
- Experience working with Calculated Insights and Computed Traits to derive meaningful business intelligence.
- Knowledge of Consent management practices and data privacy regulations.
- Familiarity with Data Streams and real-time data processing architectures.
- Ability to translate complex data requirements into technical solutions that align with business goals.