Lead Analyst - Business Intelligence & Risk Reporting

About the role

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. . 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