Ingesting lead data from APIs, forms, CSVs, and third-party partners into Salesforce
Standardizing, validating, and mapping incoming data to the correct fields
Managing deduplication using rules, fuzzy matching, or tools like DemandTools
Supporting lead source and UTM attribution for accurate marketing reporting
Improving object relationships across Leads, Contacts, Accounts, and Opportunities
Diagnosing and fixing data quality issues across Salesforce objects
Troubleshooting sync and integration problems (e.g., Zapier, Make.com webhooks)
Analyzing and optimizing our Salesforce architecture for long-term scalability
Recommending new tools, automations, or workflows to improve data operations

You’ve worked directly with outbound SDR and AE teams in a Salesforce environment
You’ve built or maintained ETL workflows to ingest and normalize lead data
You’ve managed datasets with 1M+ records and understand how to maintain CRM health at scale
You can investigate why a lead didn’t convert and trace it through multi-step logic
You’re comfortable building and adjusting attribution models (first/last touch, source UTM, campaign)
You care about data integrity and catch small issues before they become big ones
Bonus: You’ve worked with tools like Clearbit, Apollo, Unify, LinkedIn Ads, Zapier, or Make

Salesforce Data Engineer

Key skills