Salesforce Data Engineer

RESPONSIBILITIES INCLUDE: 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 duplication strategies. REQUIRED SKILLS/EXPERIENCE: Experience designing, developing and maintaining data pipelines, ETL processes, and integrations 4+ years of experience as a Salesforce Platform Developer II Salesforce Certified MuleSoft Developer (4 years) Salesforce Certified Platform Data Architect (7 years) Salesforce Certified MuleSoft Platform Architect (7 years)