Description:

Salesforce Business Analyst + CPQ + Sales Cloud

Experience 7+ years

Location Chennai (Work from Office/Work from Home)

Key Responsibilities :

- Collaborate with business stakeholders to gather, analyze, and document requirements related to Salesforce CPQ and Sales Cloud.

- Understand and explain Salesforce data model concepts, including Account, Contact, Opportunity, Quote, QuoteLine, Order, OrderItem, Subscription, and Contract.

- Provide guidance on mapping legacy data to Salesforce CPQ models, including complex relationships like product bundles.

- Recommend approaches for data cleansing, validation, and deduplication (optional).

- Suggest strategies for handling legacy data that is unstructured or spread across multiple applications (optional).

- Define strategies for retaining historical pricing, quote data, and contract renewals.

- Support User Acceptance Testing (UAT) by creating test scenarios, validating outcomes, and ensuring business requirements are met.

- Assist in validating complex fields such as Quote totals, discounts, and product configurations.

- Report and track data discrepancies, issues, or errors during system implementations or migrations (optional).

- Serve as a liaison between business teams and technical teams, translating business requirements into actionable solutions.

Required Skills and Experience :

- Strong understanding of Salesforce CPQ and Sales Cloud objects and relationships.

- Excellent analytical, documentation, and communication skills.

- Experience in requirement gathering, process analysis, and UAT coordination.

- Ability to work collaboratively with cross-functional teams and translate business needs into technical

requirements.

Optional :

- Experience in Salesforce data migration projects, including Quote, Quote Line, Order, and Order Item objects.

- Knowledge of MDM, data cleansing, deduplication, and ETL tools (Safe FME preferred).

- Familiarity with Python scripting, SQL, Snowflake, and API testing (SOAP/REST).

- Exposure data mapping, validation, and historical data retention strategies.