Lead Salesforce Data Cloud QA Engineer

Tavant; Hyderabad, Pune District, Bengaluru; Hybrid; INR 1,200,000 - 1,800,000; Full time

Job summary

Tavant is seeking a Salesforce Data Cloud QA Engineer in Hyderabad to validate end-to-end data movement and transformation across multiple source systems into Salesforce Data Cloud.

You will design and execute ETL test scenarios, perform source-to-target reconciliation with strong SQL skills, and validate data streams, mappings, and calculated insights to ensure data quality and integrity.

Qualifications

• Experience with Salesforce Data Cloud and data validation.
• Strong SQL and data reconciliation skills.
• ETL/data-pipeline testing across multiple source systems.

Responsibilities

• Test Salesforce Data Cloud capabilities and data flows end-to-end.
• Verify data ingestion and transformations from source systems into Data Cloud.
• Design and execute ETL test scenarios and regression queries.
• Validate data streams, DLOs/DMOs, mappings, and data harmonization.
• Validate identity resolution and unified customer profiles.
• Perform API and integration testing across systems.

Skills

Salesforce Data Cloud

SQL

ETL Testing

Data Validation

Data Reconciliation

APIs Testing

Integration Testing

Data Streams

Identity Resolution

Unified Profiles

CI/CD

Education

Bachelors in CS/IT/Engineering

Tools

Snowflake

Job description

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.