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Lead Salesforce Data Cloud QA Engineer

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Hybrid

Lead Salesforce Data Cloud QA Engineer

Tavant

Lead Salesforce Data Cloud QA Engineer

Skills

SQL QueriesTesting & QASnowflakeSalesforce

2 months ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Hybrid

Published on:

27 August 2026

What they need


About the Role

We are looking for a Salesforce Data Cloud QA Engineer with strong hands-on experience in data validation, ETL/data-pipeline testing, Salesforce testing, and SQL-based data reconciliation. The role focuses on validating end-to-end data movement and transformation across multiple source systems into Salesforce Data Cloud.

Salesforce Data Cloud Testing

Perform hands-on testing of Salesforce Data Cloud capabilities and data flows.

Validate data ingestion from multiple source systems into Data Cloud.

Validate Data Streams, DLOs, DMOs, mappings, transformations, and data harmonization.

Verify that source data is correctly transformed and represented within Salesforce Data Cloud.

Validate end-to-end data journeys from source systems through Data Cloud to downstream activation.

Data Validation & ETL Testing

Design and execute ETL/data-pipeline test scenarios.

Perform source-to-target validation and reconciliation using strong SQL skills.

Validate record counts, field-level mappings, data types, transformation rules, null/default handling, aggregations, business rules, and duplicate records.

Validate incremental and full data loads.

Test data refresh, synchronization, and failure/recovery scenarios.

Identify data discrepancies and trace issues across the data pipeline.

SQL & Source-to-Target Reconciliation

Develop complex SQL queries to validate data across source and target systems.

Perform reconciliation at record, field, aggregate, and business-rule levels.

Validate data completeness, accuracy, consistency, and integrity.

Analyze large datasets and identify data anomalies.

Create reusable SQL validation queries for regression testing.

Data Streams, DLO & DMO Validation

Validate Salesforce Data Cloud Data Streams and ingestion processes.

Validate DLO and DMO mappings.

Verify relationships between data objects.

Validate transformations and calculated fields.

Verify data harmonization across multiple source systems.

Test mapping changes and their downstream impact.

Identity Resolution & Unified Profiles

Validate Identity Resolution rules and matching logic.

Test duplicate and profile-matching scenarios across multiple source systems.

Validate exact matches, partial matches, conflicting attributes, missing identifiers, duplicate profiles, false matches, and multiple-source customer records.

Validate creation and maintenance of Unified Customer Profiles.

Verify that the correct customer information is consolidated across systems.

Calculated Insights & Business Rules

Validate Calculated Insights against business requirements.

Test aggregations, calculations, filters, and derived attributes.

Validate rule-based scoring and scoring thresholds.

Verify business-rule implementation and boundary conditions.

Perform positive, negative, and boundary-value testing.

Validate changes to calculations and their downstream impact.

Audience Segmentation & Activation Testing

Validate audience/segment creation based on defined business rules.

Verify segment inclusion and exclusion criteria.

Test boundary and negative scenarios for segmentation.

Validate audience counts and member profiles against expected results.

Validate activation outputs to downstream systems.

Verify that the correct profiles/data are sent to target platforms.

API & Integration Testing

Perform API and integration testing across source systems, Salesforce Data Cloud, and downstream platforms.

Validate request/response payloads, status codes, authentication, data mapping, and error handling.

Test synchronous and asynchronous integrations.

Validate retry, timeout, duplicate, and failure/recovery scenarios.

Required Skills

Salesforce Data Cloud

Strong SQL

ETL / Data Pipeline Testing

Data Warehousing and Data Testing

Source-to-target reconciliation

Data quality and validation

Data Streams, DLOs and DMOs

Identity Resolution and Unified Profiles

Calculated Insights and segmentation testing

API Testing

Integration Testing

Strong defect analysis and troubleshooting

Preferred Skills

Snowflake

Salesforce Financial Services Cloud (FSC)

Marketing Cloud Engagement

Salesforce Personalization

Financial services / mortgage domain experience

Automation testing and CI/CD experience

Education

Bachelors degree in Computer Science, Information Technology, Engineering, or a related discipline.

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