Salesforce Service Cloud-Case Management, Salesforce Service Cloud-Digital Engagement, Salesforce Service Cloud-Field Service, Salesforce Sales Cloud-Territory Planning, Salesforce Service Cloud-Self Service
Specialization
Salesforce Service Cloud: Lead Engineer
Job requirements
Experience Range: With at least 4 years of experience in data and ETL testing, including hands-on expertise with Salesforce Service Cloud and cloud data platforms Key Responsibilities: 1. Develop and execute comprehensive test strategies and cases for data pipelines, matching logic, and Salesforce Service Cloud workbench functionalities 2. Perform source-to-target and row/column reconciliation testing to ensure data accuracy and completeness throughout migration and transformation processes 3. Build and integrate automated data tests in Python within ETL and Salesforce Service Cloud pipelines to enhance validation efficiency 4. Configure and validate data quality checks using Snowflake Cortex or equivalent tools on selected cloud platforms, adapting to technology stack requirements 5. Track and manage defects throughout the testing lifecycle, verify fixes, and ensure resolutions meet business requirements 6. Report actionable data quality metrics and insights to internal teams and stakeholders, supporting continuous improvement in data reliability 7. Validate AI/ML-assisted profiling, anomaly detection, and mismatch flagging, measuring accuracy including false positives and negatives prior to business decision-making 8. Support user acceptance testing (UAT) preparation and regression testing, ensuring production validation complies with business-approved rules and controls Required Skills: 1. Advanced SQL for data validation and reconciliation 2. Hands-on experience with Salesforce Service Cloud 3. Testing experience with Snowflake or similar cloud data platforms 4. Test automation using Python, including integration with ETL pipelines 5. Proficiency in data quality testing frameworks such as Great Expectations or Soda 6. Experience testing AI/ML outputs and utilizing data quality monitoring tools Preferred Skills: 1. Salesforce data testing in complex, multi-cloud environments 2. Knowledge of advanced anomaly detection algorithms and evaluation metrics 3. Experience integrating automated test suites in CI/CD pipelines 4. Expertise configuring and optimizing Snowflake Cortex Data Quality checks 5. Familiarity with Salesforce Sales Cloud-Territory Planning best practices Desired Qualifications: 1. Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related discipline 2. Salesforce Certified Administrator or Salesforce Service Cloud Consultant certification 3. Certification in data quality or ETL testing frameworks such as Great Expectations, Soda, or equivalent
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