Lead Data & Risk Solution Analyst

Role & responsibilities:

Job Title: Lead Data & Risk Solution Analyst

Location Ggn location

Mode of work: 3 days WFO

Notice Immediate candidates who can join in Aug

Role Overview

We are looking for experienced Risk & Data professionals to support a large-scale transformation programme involving the migration of analytical EUCs / use cases from SAS to GCP.

The role will analyse individual use cases, understand the underlying business, Risk and data requirements, assess the existing GCP data landscape, and translate these requirements into engineering-ready specifications. The role will also identify opportunities to reuse and enhance existing Consumer Data Products (CDPs) across multiple use cases.

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Key Responsibilities

1. EUC & Business/Risk Analysis

• Analyse SAS-based EUCs to understand their business purpose, Risk logic, calculations, outputs and data requirements.
• Interpret SAS programs, ETL processes, macros, data flows and embedded business logic.
• Decompose complex use cases into business rules, data elements, calculations and dependencies.
• Work with Risk SMEs and stakeholders to validate requirements and resolve ambiguities.

2. GCP Data Assessment

• Assess the existing GCP data landscape to identify data elements available to support each use case.
• Determine which data can be used directly, derived, combined or added to existing data products.
• Understand data lineage, source systems, transformations, dependencies and data availability.
• Identify data gaps and articulate requirements for additional data attributes or transformations.

3. Data Requirements & Product Definition

• Translate use-case requirements into clear data requirements and specifications.
• Define required attributes, business definitions, derivations, transformations and dependencies.
• Develop source-to-target mappings and document relevant data lineage.
• Identify common data requirements across EUCs and recommend opportunities to reuse or enhance existing CDPs rather than creating duplicate data.

4. Engineering Enablement

• Produce engineering-ready specifications covering data requirements, business rules, mappings, dependencies and acceptance criteria.
• Conduct walkthroughs with Data Engineering, Architecture and Feature Pods.
• Support Engineering teams during implementation and resolve functional/data-related queries.
• Define validation and reconciliation requirements to support SAS-to-GCP migration.

5. Agile Delivery & Collaboration

• Work closely with Risk SMEs, Business Analysts, SAS/GCP Architects and Engineering teams.
• Participate in backlog refinement, sprint planning and solution walkthroughs.
• Identify dependencies, assumptions, risks and data gaps proactively.
• Contribute to reusable migration patterns, standards and knowledge assets across the migration factory.