Assistant Manager - Data Analyst / Data Strategy

Godrej Capital Limited; Mumbai, Navi Mumbai; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Godrej Capital Limited is seeking a Data Strategy and Analytics professional to independently drive business requirements from discussion to delivery, prioritizing KPI definition, data mart design, data validation, and governance. You will collaborate with Business, Product, and Data Engineering teams to build scalable data assets that support reporting, analytics, and decision making.

Manage end-to-end MIS and dashboards, and supervise a 46-analyst workload with SLA adherence.

Qualifications

• Proven ability to translate business needs into data requirements and development-ready documents.
• Experience designing KPI marts, analytical datasets, and reporting layers.
• Ability to define KPI logic, rules, calculations, and data mappings with stakeholders.
• Strong collaboration with Business, Product, and Data Engineering teams.

Responsibilities

• Gather business requirements and translate into detailed data requirements and documentation.
• Design KPI marts, analytical datasets, business views, and reporting layers aligned to objectives.
• Define KPI logic, rules, calculations, and data mappings with stakeholders.
• Work with Data Engineering to ensure accurate and scalable implementation of requirements.
• Drive discussions, feasibility assessments, dependencies, UAT, and sign-offs.
• Investigate data discrepancies with relevant teams.
• Create data dictionaries, logic documents, KPI definitions, and source-to-target mappings.
• Standardize metrics and reporting logic across functions for governance.
• Identify opportunities to optimize data structures and build reusable assets.
• Bridge Business, Analytics, BI, and Data Engineering to ensure delivery of data initiatives.
• Track progress, highlight risks, and ensure timely delivery.

Skills

KPI definition

Data mart design

Requirement gathering

Data validation

Stakeholder management

Cross-functional collaboration

SQL

Python

Tools

SQL

Python

Job description

Data Strategy-

Can independently drive business requirements from discussion to delivery. The role requires strong expertise in KPI definition, data mart design, requirement gathering, data validation, and stakeholder management. The candidate should be capable of working closely with Business, Product, and Data Engineering teams to build scalable and reusable data assets that support reporting, analytics, and decision making.

Key Responsibilities

• Gather and understand business requirements and translate them into detailed data requirements and development-ready documents.
• Design and structure KPI marts, analytical datasets, business views, and reporting layers aligned to business objectives.
• Define KPI logic, business rules, calculations, aggregations, and data mappings in consultation with stakeholders.
• Work closely with Data Engineering teams to ensure accurate and scalable implementation of requirements.
• Drive requirement discussions, feasibility assessments, dependency management, UAT, and stakeholder sign-offs.
• Investigate and resolve data discrepancies by collaborating with relevant teams.
• Create and maintain data dictionaries, logic documents, KPI definitions, and source-to-target mappings.
• Standardize metrics and reporting logic across business functions to ensure consistency and governance.
• Identify opportunities to optimize existing data structures and build reusable data assets to support multiple use cases.
• Act as the bridge between Business, Analytics, BI, and Data Engineering teams to ensure seamless delivery of data initiatives.
• Track project progress, highlight risks and dependencies, and ensure timely delivery of requirements.

Data Analytics-

Manage the end-to-end reporting processes, including data extraction, transformation, and presentation.

• Ensure overnight MIS jobs, and dashboards run successfully; troubleshoot failures in SQL/Python.
• Distribute workload across 46 analysts, set priorities, and monitor SLA adherence.
• Interact with different teams (sales, risk, operations, credit, audit, product, etc.) – clarify requests.
• Decide which requests need immediate delivery, which can be automated, and which should be declined/redirected.
• Effective management of business-critical support requests during late evenings / early mornings / holidays (beyond working hours)
• Hands‑on debugging when issues arise in Python scripts, SQL queries, or dashboards.