Conduct deep-dive audits of client Salesforce data to identify duplicates, inconsistencies, and structural gaps.
Lead the hands-on configuration of data management tools such as DataGroomr, Cloudingo, or DemandTools.
Design and execute complex deduplication logic, ensuring that merging records does not break critical relationships with Subscriptions, Opportunities, or Account Products.
Establish Master Data Management governance models to ensure data remains "clean" post-migration.
Ensure data is structured correctly for seamless synchronization with downstream systems like NetSuite or other ERPs.
Manage how data cleaning operations interact with existing Salesforce Flows, Triggers, and validation rules to avoid system conflicts.
Implement automated processes for data normalization (address validation, phone formatting, industry mapping).
Build Data Health Dashboards to provide real-time visibility into data accuracy and the progress of cleanup initiatives.
Requirements
3+ years of hands-on experience in Salesforce data management and data quality roles.
Expert knowledge of Salesforce architecture: You must understand object relationships, External IDs, and the impact of data merging on the wider CRM ecosystem.
Specialized Tool Expertise: Deep proficiency in at least one industry-leading cleaning tool: DataGroomr, Cloudingo, or DemandTools.
Data-Driven Mindset: You enjoy finding "needles in haystacks" and have a relentless focus on accuracy and detail.
Consulting DNA: Comfortable in client-facing roles, able to explain complex data risks to non-technical stakeholders in terms of ROI and business impact.
Execution-Focused: You thrive in fast-paced, PE-backed environments where "getting stuff done" with precision is the standard.
Salesforce Certified: Salesforce Administrator or Data Architecture certifications are a significant plus.
Benefits
Opportunity to work on large-scale data transformations for global enterprise clients.
Exposure to the latest AI-driven data grooming technologies and enterprise architectures.
High autonomy and ownership over data strategy and delivery outcomes.
Global, collaborative team focused on innovation and measurable results.