Lead Analyst – Business Intelligence & Risk Reporting

This role sits at the core of our credit risk business intelligence and risk reporting ecosystem, owning the quality, structure, and reliability of data that powers portfolio insights, risk reporting, and decision-making. By strengthening data foundations through advanced SQL, robust transformations, and rigorous controls, this role directly improves accuracy, explain ability, and trust in risk analytics used by senior leadership. You’ll work on high-impact, real-world credit risk data at scale—solving complex data problems, influencing how risk is measured and understood, and building data assets that are reused across multiple analytics and reporting teams. This is a role for someone who wants to own the data, not just consume it.

Job Details

• Position Title:  Lead Analyst – Business Intelligence & Risk Reporting

• Career Level:  P3

• Job Category: Manager

• Role Type: Hybrid

• Job Location: Bangalore  

About the Team:

We are a team of skilled professionals with proven expertise in delivering analytical and reporting solutions that transform raw data into actionable insights. With 75% of our team from risk analytics background and the rest equipped with advanced analytical skills. We ensure data and metrics are timely, traceable, and consistent to drive impactful decisions.

Impact

This role materially improves the accuracy, consistency, and reliability of credit risk data, enabling faster, more confident decision-making across portfolio management, risk monitoring, and senior leadership reporting. You will work on building scalable, reusable data assets that can be consumed across multiple analytics use cases

Key Deliverables

Analytics-ready credit risk datasets – Development of reusable, scalable, curated, well-structured datasets for downstream analytics and reporting consumption.

Robust SQL transformation logic - Production-grade SQL scripts handling complex joins, aggregations, windowing, and performance optimization across large, multi-source datasets.

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Automated data preparation pipelines - Repeatable data transformation workflows built using Tableau Prep to minimize manual intervention and reduce operational risk.

Reusable data assets & datasets - Common, documented data layers and views that can be reused across analytics, reporting, and ad-hoc use cases.

Python-based analytics support- Scripts for data wrangling, exploratory analysis, validation, and automation of recurring analytical tasks.

Data documentation & lineage artefacts - Clear documentation of source-to-target mappings, transformation logic, assumptions, and data dependencies.

Issue resolution & root-cause analysis - Timely identification and resolution of data anomalies, with clear explanations shared with stakeholders

Skills and Qualification

 Functional Skills:

• Strong understanding of credit risk data and banking domain

• Strong data validation, reconciliation, and control mindset

• Ability to explain portfolio movements, variances, and anomalies using data

• Experience working with multiple upstream data sources and resolving data inconsistencies

• Understanding of data lineage, metadata, and transformation logic

• Stakeholder collaboration with risk, analytics, finance, and technology teams

• Structured problem-solving and root-cause analysis skills

• Strong documentation and knowledge-sharing capability

• Analytical mindset with an eye for both detail and big-picture context

Technical Skills

• 7+ years of relevant experience in the field of data wrangling and data engineering

• Proven knowledge and deep understanding of writing complex, optimized SQLs

• Experience in building end-to-end data preparation and transformation flow using Tableau Prep

• Basic understanding of Alteryx – data blending, transformation, and workflow automation

• Hands-on experience in data wrangling, validation, exploratory analysis, and automation techniques using Python

• Familiarity with data analysis and reporting tools (Excel, SQL, Tableau)

• Experience with version control (Git)

• Data Concepts

  • Relational data modeling and normalization

  • Handling large-volume datasets

  • Data quality, controls, and reconciliation techniques

Relationships & Collaboration

Reports to: Senior Manager – Business Intelligence and Risk Reporting

Partners: Data developers, Dashboard developers, Data Product teams, Data Infrastructure team, and cross-functional teams.

Accessibility Needs

We are committed to providing an inclusive and accessible hiring process. If you require accommodations at any stage (e.g. application, interviews, onboarding) please let us know, and we will work with you to ensure a seamless experience.