Manager, Salesforce Data Engineering

About the Role

The Manager, Salesforce Data Engineering leads a team of Salesforce system engineers responsible for building and supporting reliable, secure, and scalable data solutions across Salesforce and connected enterprise systems. This role will immediately own two critical workstreams: Dual Org Sync , the Salesforce-to-Salesforce integration connecting our two Salesforce orgs, and Data Migration , our Salesforce-to-Salesforce migration efforts, while managing, mentoring, and growing the engineers who deliver them. The ideal candidate combines hands-on Salesforce platform development and integration experience with proven team leadership, and is fluent in applying cutting-edge AI technologies to real engineering work.

What You’ll Do

• Own and lead the Dual Org Sync workstream, the Salesforce-to-Salesforce integration between our two Salesforce orgs, ensuring reliable, secure, and scalable data flow across systems.
• Own and lead the Data Migration workstream, driving Salesforce-to-Salesforce migration efforts from planning through cutover with strong data integrity and minimal business disruption.
• Lead the design, delivery, and support of Salesforce data solutions that are scalable, reliable, secure, and maintainable.
• Translate business needs into practical technical plans across data modeling, integrations, migrations, transformations, automation, and operational support.
• Lead and manage a team of engineers, including hiring, onboarding, workforce planning, regular feedback, performance management, and career development.
• Partner with product, business stakeholders, engineering, QA, data warehouse, and data quality teams to align priorities, manage risk, and deliver successful outcomes.
• Champion the adoption of cutting-edge AI technologies within the team, applying AI-powered tools and agentic approaches beyond basic chat use, to automate workflows, accelerate delivery, and strengthen data quality.
• Improve platform health by simplifying data flows, reducing technical debt, strengthening data quality controls, and improving observability and supportability.
• Guide technical decisions through design reviews, code and automation reviews, troubleshooting, and knowledge sharing.
• Create and maintain documentation for data models, system relationships, data flows, dependencies, support procedures, and operational considerations, while fostering a collaborative, inclusive team culture.

What You’ll Bring

• 8+ years of experience in software/data engineering, with 4+ years developing on the Salesforce platform.
• 2+ years of people management experience leading data engineering or Salesforce engineering teams, including hiring, performance management, and career development.
• Proven experience designing, delivering, and supporting integrations, migrations, transformations, reconciliations, and monitoring across Salesforce and enterprise systems; direct hands-on experience with Salesforce-to-Salesforce integrations and org-to-org data migrations strongly preferred.
• Hands-on experience developing on the Salesforce platform ( Apex , Lightning Components , Flow , and related tools), with strong expertise in Salesforce data modeling , SQL , SOQL , CPQ architectures , security, automation, platform design patterns, and data lifecycle management.
• Experience with enterprise ETL or data movement tools, such as dbAmp or similar platforms.
• Demonstrated, hands-on proficiency with cutting-edge AI technologies , such as building or deploying AI agents, LLM-powered automation , or applied AI/ML tooling in engineering workflows, beyond general-purpose chat usage.
• Strong strategic prioritization and problem-solving skills, including triage, debugging, performance optimization, root cause analysis, and incident support.
• Clear communication and collaboration skills, with the ability to influence technical direction and align senior stakeholders across technical and non-technical teams.

Bonus Skills

• Salesforce Administrator , Platform App Builder , or Salesforce Platform Developer certifications required.
• Bachelor’s degree in Computer Science , Information Systems , Engineering , Data Engineering , or a related field preferred; equivalent practical experience also considered.
• Demonstrated application of AI/agentic tooling in professional projects (portfolio, case studies, or concrete examples) strongly preferred.