Salesforce Data Engineer

• Design, develop, and maintain scalable data pipelines, extract transform and load (ETL) processes, integrations, and APIs between Salesforce and external systems
• Optimize data ingestion and transformation processes in alignment with best practices for Salesforce data architecture.
• Define and implement data storage, normalization, and performance strategies across Salesforce instances.
• Lead the data modeling strategy across Salesforce Clouds, including Public Sector Cloud, Service Cloud, and Experience Cloud.
• Monitor and manage data migration, deduplication, and cleansing efforts to ensure system consistency and integrity.
• Design and deploy AI-powered agents that interact with Salesforce data for dynamic decision support, customer service, and workflow automation.
• Collaborate with AI/ML specialists to integrate predictive models and generative AI assistants within Salesforce environments (e.g., Einstein GPT or other LLM-based tools).
• Coordinate the implementation of data governance frameworks and best practices across client organizations, with a focus on Salesforce data ecosystems.

• Work with the Salesforce product owner, business units, and stakeholders to align data governance requirements and strategies.
• Support the development and enforcement of data standards, naming conventions, data ownership, and stewardship models including business glossaries, data dictionaries, and metadata for key Salesforce data assets.
• Provide documentation and guidance for Salesforce data integrations, data cleansing initiatives, and deduplication strategies.

Experience:

• Salesforce Platform Developer II (4-6 years)
• Salesforce Certified MuleSoft Developer (4-6 years)
• Salesforce Certified Platform Data Architect (7-9 years)
• Salesforce Certified MuleSoft Platform Architect (7-9 years)