Senior Engineer, Customer Data Platform
Tasks
- Build AI powered customer engagement solutions
- Build REST API and GraphQL integrations
- Build unified customer profiles
- Collaborate with marketing, CRM, and product teams
- Configure identity resolution rules
- Configure marketing cloud personalization
- Create technical documentation
- Design Salesforce Data Cloud solutions
- Design scalable ETL/ELT pipelines
- Develop customer segments and activation strategies
- Develop reusable services and APIs
- Implement Agentforce agents and automation
- Implement CI/CD pipelines
- Implement consent management and privacy controls
- Implement event driven customer data pipelines
- Integrate Data Cloud with data warehouses and lakehouses
- Integrate predictive audiences and propensity models
- Optimize ingestion performance and data quality
- Set up monitoring alerting and dashboards
- Troubleshoot production issues
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Activation | Azure | Azure DevOps | CCPA | CI/CD | Calculated Insights | Cloud Data | Cloud data warehousing | Cloud engagement | Commerce Cloud | Customer Data | Customer data platforms | Customer identity | Customer identity resolution | Data Lakes | Data Model | Data Model Objects | Data Streams | Data Warehousing | Data cloud | Data graphs | Data platforms | Databricks | ELT | ETL | Einstein AI | Event Driven | Event-driven architecture | Experience Cloud | GDPR | Gearset | GitHub | GraphQL | Identity matching | Identity resolution | Interaction Studio | JSON | Kafka | Kinesis | Lakehouse Federation | Marketing Cloud | Marketing Cloud Engagement | Marketing Cloud Personalization | MuleSoft | Python | REST APIs | SQL | Sales Cloud | Salesforce Agentforce | Salesforce Data Cloud | Salesforce data | Segmentation | Service Cloud | Snowflake
Education
N/A
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