Hybrid Data Cloud Integration Product Manager

Spectraforce Technologies, Inc.; East Hanover (NJ); Hybrid; USD 140,000 - 170,000; Full time

Job summary

Spectraforce Technologies, Inc. seeks a Data Cloud Integration Product Manager to lead enterprise data integration efforts within the US CRM organization. You will convert business demand into a prioritized backlog, define reusable integration patterns, and coordinate architecture and delivery with multiple teams.

The role emphasizes data fluency, stakeholder partnership, and the ability to translate business needs into scalable technical requirements for Data Cloud across Data Spaces.

Qualifications

• Bachelor's degree required (data/tech/engineering).
• 5+ years in product management, data integration, or related areas.
• Strong knowledge of data integration concepts, APIs, batch/streaming pipelines, and data contracts.
• Hands-on understanding of Salesforce Data Cloud, Data Streams, and activation workflows.
• Experience leading an agile backlog and coordinating across teams.

Responsibilities

• Manage integration intake: qualify requests for new Data Streams and shared data products.
• Shape enterprise priorities and plan pipeline work across Data Streams and Data Lakes.
• Define integration scope with epics, features, and data contracts.
• Own shared integration backlog and ensure backlog readiness for planning.
• Lead build and lifecycle management of data pipelines and cross-space analytics.
• Ensure data quality, lineage, and monitoring for shared integrations.

Skills

Data integration

Agile backlog management

Stakeholder collaboration

Data quality

Data modeling

Education

Bachelor's degree in data/tech

Tools

Salesforce Data Cloud

Snowflake

CI/CD tooling

Job description

Spectraforce Technologies, Inc. seeks a Data Cloud Integration Product Manager to lead enterprise data integration efforts within the US CRM organization. You will convert business demand into a prioritized backlog, define reusable integration patterns, and coordinate architecture and delivery with multiple teams.

The role emphasizes data fluency, stakeholder partnership, and the ability to translate business needs into scalable technical requirements for Data Cloud across Data Spaces.