Salesforce Data Cloud Engineer

Job Summary

Design and implement unified customer data platforms using Salesforce Data Cloud, focusing on scalable identity resolution pipelines. Develop and optimize data pipelines including Data Streams, Data Model Objects (DMOs), and Calculated Insights to support high-quality customer profiles. Build audience segmentation and activation workflows for Marketing Cloud, advertising, sales/service, and commerce platforms. Define and execute identity resolution strategies (deterministic & probabilistic) to create accurate golden records and improve data completeness. Implement data governance and privacy compliance practices, including consent modeling and PII/PHI protection. Partner with marketing, product, and CRM teams to translate business requirements into data models, insights, and activation workflows. Establish CI/CD processes and automated data quality checks, monitoring, lineage, and SLA reporting for data pipelines. Integrate Salesforce Data Cloud with analytics and ML platforms (e.g., Amazon Redshift, Databricks). Utilize strong SQL skills and modern data engineering techniques in building and maintaining data infrastructure. Work with ETL/ELT pipelines, streaming technologies (Kafka/Kinesis), APIs, and Git-based CI/CD workflows. Support customer data activation across multiple platforms, ensuring high data quality and compliance.

Preferred Qualifications

• Experience with Python/dbt
• MDM tools
• Reverse ETL pipelines
• Amazon Redshift
• ML operationalization (Einstein Studio/Copado)

Top Skills

• Salesforce Data Cloud
• SQL
• CRM / Customer Data Platforms (CDP)
• Identity Resolution
• Data Pipeline Engineering
• Data Privacy & Consent Management

Required Experience

• 5+ years in data engineering, CRM, or CDP
• 2+ years with Salesforce Data Cloud or similar CDP
• Experience in segmentation, activation workflows, and data governance