Salesforce Data Architect

About the role

The Salesforce Data Architect at Cirrius Solutions owns the data architecture for enterprise Salesforce implementations - from the core platform data model through migration, governance, and security, to integration with the client’s broader data ecosystem. This is a senior technical role: the Data Architect designs how data is structured, secured, moved, and governed across Salesforce and the enterprise data platform (a Databricks lakehouse), and partners closely with delivery pods, solution and integration architects, and client data teams.

Responsibilities

• Own the Salesforce data model - objects, relationships, and record structures - designing for scale, reporting, and long-term maintainability
• Design and govern the data migration strategy: source-to-target mapping, ETL/ELT pipelines, deduplication, cleansing, validation, and cutover planning from legacy systems into Salesforce
• Arcitect the integration between Salesforce and the enterprise data platform (Databricks lakehouse) - including zero-copy / Delta Sharing and federation patterns, bidirectional data flows, and curated pipelines so data is shared without unnecessary duplication
• Define data governance, data quality, and master data management (MDM) standards - ownership, stewardship, survivorship rules, and reference data management across Salesforce and the lakehouse
• Design the Salesforce security and sharing model - org-wide defaults, role hierarchy, sharing rules, field-level security, and encryption (Shield) - to meet least-privilege and compliance requirements
• Arcitect for Large Data Volumes (LDV): indexing, selective queries, skinny tables, archiving, and purge/retention strategies
• Design the analytics and reporting data architecture, including how curated lakehouse data (medallion / bronze-silver-gold) feeds dashboards and how insights are activated back into Salesforce
• Establish data lifecycle, backup/archival, and retention policies aligned to regulatory requirements (e.g., GDPR, CCPA)
• Produce architecture documentation, data dictionaries, and design decision records, and set the data standards the delivery pods build against
• Partner with solution architects, integration architects, delivery pods, and client data engineering teams; present and defend data design decisions to technical and business stakeholders

Requirements

• Experience with Salesforce Certified Data Architect, Salesforce Certified Application Architect or System Architect
• 7+ years of enterprise data experience, including hands-on Salesforce data architecture
• Deep expertise in Salesforce data modeling, standard and custom objects, relationships, and the platform security and sharing model
• Proven data migration experience: ETL/ELT tooling, source-to-target mapping, large-scale loads, and data quality, deduplication, and validation
• Hands-on experience integrating Salesforce with a cloud data platform or lakehouse - Databricks strongly preferred (Delta Lake, Delta Sharing, Unity Catalog, and zero-copy / federation patterns)
• Strong understanding of Large Data Volume (LDV) considerations and query and performance optimization on the Salesforce platform
• Experience with data governance, master data management (MDM), and data quality frameworks
• Working knowledge of SQL and data transformation; familiarity with Spark and notebook-based development a plus
• Understanding of integration patterns (REST/Bulk APIs, Platform Events, Change Data Capture) and how they affect data architecture
• Effective communication skills with both technical teams and business/executive stakeholders
• Ability to support multiple engagements and delivery pods simultaneously

Bonus Skills

• Databricks certification (e.g., Databricks Certified Data Engineer Associate/Professional)
• Experience with the Salesforce Data Cloud
• Experience with CRM Analytics and/or Tableau for reporting on Salesforce and lakehouse data
• Experience with Shield Platform Encryption and regulatory compliance (GDPR, CCPA, HIPAA)
• ETL / data pipeline tooling experience (e.g., MuleSoft, Informatica, Talend, dbt, or Fivetran)